1 the ontology of experiments + pato barry smith
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1
The Ontology of Experiments+ PATO
Barry Smith
httpontologybuffaloedusmith
2
Plan
1 The Experiment Ontology
2 Upper Level Ontologies
3 The Ontology of Biomedical Investigations
4 Phenotype Ontology
3
EXPO
The Ontology of Experiments
L Soldatova R KingDepartment of Computer Science
The University of Wales Aberystwyth
4
EXPO
controlled vocabularymeta-modeltheory of contentknowledge management10487081048708 knowledge systematization10487081048708 knowledge sharing10487081048708 knowledge treatment10487081048708 knowledge reusabilitydata integration
5
EXPO Formalisation of Science
The goal of science is to increase our knowledge of the natural world through the performance of experiments
This knowledge should ideally be expressed in a formal logical language
Formal languages promote semantic clarity which in turn supports the free exchange of scientific knowledge and simplifies scientific reasoning
6
7
8
9
Suggested Upper Merged Ontology
Adam Peaseapeasearticulatesoftwarecomhttpwwwarticulatesoftwarecom
10
SUMO top levelEntity
ndash Physical bull Object
ndash SelfConnectedObject raquo Substance raquo CorpuscularObject raquo Food
ndash Region ndash Collection ndash Agent
bull Process ndash Abstract
bull SetOrClass bull Relation bull Quantity
ndash Number ndash PhysicalQuantity
bull Attribute bull Proposition
11
Suggested Upper Merged Ontology
1000 terms 4000 axioms 750 rules
Associated domain ontologies totalling 20000 terms and 60000 axioms
[includes ontology of boundaries from BS]
12
SUMO Structure
Structural Ontology
Base Ontology
SetClass Theory Numeric Temporal Mereotopology
Graph Measure Processes Objects
Qualities
13
SUMO+Domain OntologyStructuralOntology
BaseOntology
SetClassTheory
Numeric Temporal Mereotopology
Graph Measure Processes Objects
Qualities
SUMO
Mid-Level
Military
Geography
Elements
Terrorist Attack Types
Communications
People
TransnationalIssues Financial
Ontology
TerroristEconomy
NAICSTerroristAttacks
hellip
FranceAfghanistan
UnitedStates
DistributedComputing
BiologicalViruses
WMD
ECommerceServices
Government
Transportation
WorldAirports
Total Terms Total Axioms Rules
20399 67108 2500
14
entity physical object process dual object process intentional process intentional psychological process recreation or exercise organizational process guiding keeping maintaining repairing poking content development making constructing manufacture publication cooking searching social interaction maneuver motion internal change shape change abstract
15
corpuscular object =defA SelfConnectedObject whose parts have properties that are not shared by the whole
Subclass(es)organic object artifact
Coordinate term(s)content bearing object food substance
Axiom corpuscular object is disjoint from substance
substance =defAn Object in which every part is similar to every other in every relevant respect
16
advantages of SUMO
clear logical infrastructure FOL (too expressive for decidability more intuitive (human friendly) than eg OWL)
much more coherent than eg CYC upper level
much more coherent than the upper level hard wired into OWL-DL (and a fortiori into OWL-FULL)
FOL
17
problems with SUMO as Upper-Levelit contains its own tiny biology (protein
crustacean fruit-Or-vegetable )
it is overwhelmingly an ontology for abstract entities (sets functions in the mathematical sense )
no clear treatment of relations between instances vs relations between types
[all of these problems can be fixed]
18EXPO Experiment Ontology
19
representational style part_of experimental hypothesisexperimental actions part_of experimental design
20equipment part_of experimental design(confuses object with specification)
21
22
OBI
The Ontology of Biomedical Investigations
grew out of FuGE FuGO MGED PSI development activities
23
Overview of the Ontology of Biomedical Investigations
with thanks to Trish Whetzel (FuGO Working Group)
24
OBI neacutee FuGOPurpose
Provide a resource for the unambiguous description of the components of biomedical investigations such as the design protocols and instrumentation material data and types of analysis and statistical tools applied to the data NOT designed to model biology
Enables consistent annotation of data across different
technological and biological domains powerful queries semantically-driven data integration
25
Motivation for OBI
Standardization efforts in biological and technological domains Standard syntax - Data exchange formats
To provide a mechanism for software interoperability eg FuGE Object Model
Standard semantics - Controlled vocabularies or ontology Centralize commonalities for annotation term
needs across domains to describe an investigationstudyexperiment eg FuGO
26
Emerging FuGO Design Principles
OBO Foundry ontology utilize ontology best practices Inherit top level classes from an Upper Level ontology Use of the Relation Ontology Follow additional OBO Foundry principles Facilitates interoperability with other OBO Foundry
ontologiesOpen source approach
ProteacutegeacuteOWL Weekly conference calls Shared environment using Sourceforge (SF) and SF
mailing lists
27
OBI Collaborating CommunitiesCrop sciences Generation Challenge Programme (GCP)Environmental genomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiGenomic Standards Consortium (GSC)
wwwgenomicscehacukgenomecatalogueHUPO Proteomics Standards Initiative (PSI) psidevsourceforgenetImmunology Database and Analysis Portal wwwimmportorgImmune Epitope Database and Analysis Resource (IEDB)
httpwwwimmuneepitopeorghomedoInternational Society for Analytical Cytology httpwwwisac-netorgMetabolomics Standards Initiative (MSI) Neurogenetics Biomedical Informatics Research Network (BIRN)Nutrigenomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiPolymorphismToxicogenomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiTranscriptomics MGED Ontology Group
28
29
30
FuGO - Top Level Universals Continuant an entity that endureremains the same through time
bull Dependent Continuant depend on another entityEg Environment (depend on the set of ranges of conditions eg geographic location)
Eg Characteristics (entity that can be measured eg temperature unit)
- Realizable an entity that is realizable through a process (executedrun)Eg Software (a set of machine instructions)
Eg Design (the plan that can be realized in a process)
Eg Role (the part played by an entity within the context of a process)
bull Independent Continuant stands on its ownEg All physical entity (instrument technology platform document etc)
Eg Biological material (organism population etc)
Occurrent an entity that occursunfold in timebull Eg Temporal Regions Spatio-Temporal Regions (single actions or Event)
bull Process Eg Investigation (the entire lsquoexperimentalrsquo process)Eg Study (process of acquiring and treating the biological material)Eg Assay (process of performing some tests and recording the results)
31
32
33
Basic Formal Ontologya true upper level ontologyno interference with domain ontologiesno interference with physics cognitionno abstractano negative entitiesexplicit treatment of instances types and relations
34
Three dichotomies
instance vs type
continuant vs occurrent
dependent vs independent
everything in the ontology is a type
types exist in reality through their instances
35
instance vs type
experiments as instances
experiments as types
ontologies relate to types (kinds universals)
we need to keep track of instances in databases
36
BFO
ContinuantOccurrent(Process)
IndependentContinuant
DependentContinuant
37
BFO
ContinuantOccurrent(Process)
IndependentContinuant
(molecule cell organorganism)
DependentContinuant
(quality functiondisease)
Functioning Side-Effect Stochastic Process
38
BFO
ContinuantOccurrent(Process)
IndependentContinuant
(molecule cell organorganism)
PATO Functioning Side-Effect Stochastic Process
39
Unifying goal integration
Integrating datandash within and across these domainsndash across levels of granularityndash across different perspectives
Requiresndash Rigorous formal definitions in both ontologies
and annotation schemas
40
Some thoughts on the ontology itself
Outlinendash Definitions
bull how do we define PATO termsbull what exactly is it wersquore defining
ndash is_a hierarchybull what are the top-level distinctionsbull what are the finer grained distinctions
ndash shapes and colors
41
Itrsquos all about the definitions
OBO Foundry Principlendash Definitions should describe things in reality
not how terms are usedbull definitions should not use the word lsquodescribingrsquo
Scope of PATO = Phenotypic qualities
42
Old PATOEntity ndash Attribute ndash Value
Eye ndash Red ndash Dark
New PATOEntity ndash Quality
Eye ndash Red Eye ndash Dark Red
Dark Red is_a Red
43
What a quality is NOT
Qualities are not measurementsndash Instances of qualities exist independently of their
measurementsndash Qualities can have zero or more measurements
These are not the names of qualitiesndash percentagendash processndash abnormalndash high
44
Some examples of qualities
The particular redness of the left eye of a single individual flyndash An instance of a quality type
The color lsquoredrsquondash A quality type
Note the eye does not instantiate lsquoredrsquo
PATO represents quality types (universals)ndash PATO definitions can be used to classify quality
instances by the types they instantiate
45
the particular case ofredness (of a particularfly eye)
the type ldquoredrdquo
instantiates
an instance of an eye(in a particular fly)
the type ldquoeyerdquo
instantiates
inheresin (is aquality ofhas_bearer)
46
Qualities are dependent entities
Qualities require bearersndash Bearers can be physical objects or processes
Examplendash A shape requires a physical object to bear itndash If the physical object ceases to exist (eg it
decomposes) then the shape ceases to exist
48
Scale Bearer Quality Definition (proposed)
Physical Continuant Mass Equivalent to the sum of the mass of the parts of the bearer (mass at the particle level is primitiveoutwith PATO)
Physical Continuant Opacity An optical quality manifest by the capacity of the bearer to block light
PhysChem Liquid Concentration A compositional relational quality manifest by the relative quantity of some chemical type contained by the bearer
Molecular Gene splicing quality manifest by the splicing processes undergone by the bearer
Cellular Cell ploidy A cellular quality manifest by the number of genomes that are part of the bearer
Cellular Cell transformative potency
A cellular quality manifest by the capacity of the bearer cell to differentiate to different cell types
Organismal Tissue tone
Organismal Organism reproductive quality
49
How many types of shape are there
notched T-shaped Y-shaped branched unbranched antrose retrose curled curved wiggly squiggly round flat square oblong elliptical ovoid cuboid spherical egg-shaped rod-shaped heart-shaped hellip
How do we define them
How do we compare them
Shapes cannot be organized in a linear scale
Compare problem of classifying RNA structures
50
Standard case monadic qualitiesExamples
ndash E=kidney Q=hypertrophiedndash autodef a kidney which is hypertrophied
We assume that there is more contextual data (not shown)ndash eg genotype environment number of organisms
in study that showed phenotype
Interpretation (with the rest of the database record)ndash all fish in this experiment with a particular
genotype had a hypertrophied kidney at some point in time
51
Who should use PATO
Originallyndash model organism mutant phenotypes
But alsondash ontology-based evolutionary systematicsndash neuroscience BIRNndash clinical uses
bull OMIMbull clinical records (clinical manifestations)bull drug effects chemical effects
ndash to define terms in other ontologiesbull eg diploid cell invasive tumor engineered gene
condensed chromosome
- The Ontology of Experiments + PATO
- Plan
- EXPO
- Slide 4
- EXPO Formalisation of Science
- Slide 6
- Slide 7
- Slide 8
- Suggested Upper Merged Ontology
- SUMO top level
- Suggested Upper Merged Ontology
- SUMO Structure
- SUMO+Domain Ontology
- Slide 14
- Slide 15
- advantages of SUMO
- problems with SUMO as Upper-Level
- Slide 18
- Slide 19
- Slide 20
- Slide 21
- OBI
- Overview of the Ontology of Biomedical Investigations
- OBI neacutee FuGO
- Motivation for OBI
- Emerging FuGO Design Principles
- OBI Collaborating Communities
- Slide 28
- Slide 29
- FuGO - Top Level Universals
- Slide 31
- Slide 32
- Basic Formal Ontology
- Three dichotomies
- instance vs type
- BFO
- Slide 37
- Slide 38
- Unifying goal integration
- Some thoughts on the ontology itself
- Itrsquos all about the definitions
- Old PATO Entity ndash Attribute ndash Value Eye ndash Red ndash Dark
- What a quality is NOT
- Some examples of qualities
- Slide 45
- Qualities are dependent entities
- Slide 48
- How many types of shape are there
- Standard case monadic qualities
- Who should use PATO
-
2
Plan
1 The Experiment Ontology
2 Upper Level Ontologies
3 The Ontology of Biomedical Investigations
4 Phenotype Ontology
3
EXPO
The Ontology of Experiments
L Soldatova R KingDepartment of Computer Science
The University of Wales Aberystwyth
4
EXPO
controlled vocabularymeta-modeltheory of contentknowledge management10487081048708 knowledge systematization10487081048708 knowledge sharing10487081048708 knowledge treatment10487081048708 knowledge reusabilitydata integration
5
EXPO Formalisation of Science
The goal of science is to increase our knowledge of the natural world through the performance of experiments
This knowledge should ideally be expressed in a formal logical language
Formal languages promote semantic clarity which in turn supports the free exchange of scientific knowledge and simplifies scientific reasoning
6
7
8
9
Suggested Upper Merged Ontology
Adam Peaseapeasearticulatesoftwarecomhttpwwwarticulatesoftwarecom
10
SUMO top levelEntity
ndash Physical bull Object
ndash SelfConnectedObject raquo Substance raquo CorpuscularObject raquo Food
ndash Region ndash Collection ndash Agent
bull Process ndash Abstract
bull SetOrClass bull Relation bull Quantity
ndash Number ndash PhysicalQuantity
bull Attribute bull Proposition
11
Suggested Upper Merged Ontology
1000 terms 4000 axioms 750 rules
Associated domain ontologies totalling 20000 terms and 60000 axioms
[includes ontology of boundaries from BS]
12
SUMO Structure
Structural Ontology
Base Ontology
SetClass Theory Numeric Temporal Mereotopology
Graph Measure Processes Objects
Qualities
13
SUMO+Domain OntologyStructuralOntology
BaseOntology
SetClassTheory
Numeric Temporal Mereotopology
Graph Measure Processes Objects
Qualities
SUMO
Mid-Level
Military
Geography
Elements
Terrorist Attack Types
Communications
People
TransnationalIssues Financial
Ontology
TerroristEconomy
NAICSTerroristAttacks
hellip
FranceAfghanistan
UnitedStates
DistributedComputing
BiologicalViruses
WMD
ECommerceServices
Government
Transportation
WorldAirports
Total Terms Total Axioms Rules
20399 67108 2500
14
entity physical object process dual object process intentional process intentional psychological process recreation or exercise organizational process guiding keeping maintaining repairing poking content development making constructing manufacture publication cooking searching social interaction maneuver motion internal change shape change abstract
15
corpuscular object =defA SelfConnectedObject whose parts have properties that are not shared by the whole
Subclass(es)organic object artifact
Coordinate term(s)content bearing object food substance
Axiom corpuscular object is disjoint from substance
substance =defAn Object in which every part is similar to every other in every relevant respect
16
advantages of SUMO
clear logical infrastructure FOL (too expressive for decidability more intuitive (human friendly) than eg OWL)
much more coherent than eg CYC upper level
much more coherent than the upper level hard wired into OWL-DL (and a fortiori into OWL-FULL)
FOL
17
problems with SUMO as Upper-Levelit contains its own tiny biology (protein
crustacean fruit-Or-vegetable )
it is overwhelmingly an ontology for abstract entities (sets functions in the mathematical sense )
no clear treatment of relations between instances vs relations between types
[all of these problems can be fixed]
18EXPO Experiment Ontology
19
representational style part_of experimental hypothesisexperimental actions part_of experimental design
20equipment part_of experimental design(confuses object with specification)
21
22
OBI
The Ontology of Biomedical Investigations
grew out of FuGE FuGO MGED PSI development activities
23
Overview of the Ontology of Biomedical Investigations
with thanks to Trish Whetzel (FuGO Working Group)
24
OBI neacutee FuGOPurpose
Provide a resource for the unambiguous description of the components of biomedical investigations such as the design protocols and instrumentation material data and types of analysis and statistical tools applied to the data NOT designed to model biology
Enables consistent annotation of data across different
technological and biological domains powerful queries semantically-driven data integration
25
Motivation for OBI
Standardization efforts in biological and technological domains Standard syntax - Data exchange formats
To provide a mechanism for software interoperability eg FuGE Object Model
Standard semantics - Controlled vocabularies or ontology Centralize commonalities for annotation term
needs across domains to describe an investigationstudyexperiment eg FuGO
26
Emerging FuGO Design Principles
OBO Foundry ontology utilize ontology best practices Inherit top level classes from an Upper Level ontology Use of the Relation Ontology Follow additional OBO Foundry principles Facilitates interoperability with other OBO Foundry
ontologiesOpen source approach
ProteacutegeacuteOWL Weekly conference calls Shared environment using Sourceforge (SF) and SF
mailing lists
27
OBI Collaborating CommunitiesCrop sciences Generation Challenge Programme (GCP)Environmental genomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiGenomic Standards Consortium (GSC)
wwwgenomicscehacukgenomecatalogueHUPO Proteomics Standards Initiative (PSI) psidevsourceforgenetImmunology Database and Analysis Portal wwwimmportorgImmune Epitope Database and Analysis Resource (IEDB)
httpwwwimmuneepitopeorghomedoInternational Society for Analytical Cytology httpwwwisac-netorgMetabolomics Standards Initiative (MSI) Neurogenetics Biomedical Informatics Research Network (BIRN)Nutrigenomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiPolymorphismToxicogenomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiTranscriptomics MGED Ontology Group
28
29
30
FuGO - Top Level Universals Continuant an entity that endureremains the same through time
bull Dependent Continuant depend on another entityEg Environment (depend on the set of ranges of conditions eg geographic location)
Eg Characteristics (entity that can be measured eg temperature unit)
- Realizable an entity that is realizable through a process (executedrun)Eg Software (a set of machine instructions)
Eg Design (the plan that can be realized in a process)
Eg Role (the part played by an entity within the context of a process)
bull Independent Continuant stands on its ownEg All physical entity (instrument technology platform document etc)
Eg Biological material (organism population etc)
Occurrent an entity that occursunfold in timebull Eg Temporal Regions Spatio-Temporal Regions (single actions or Event)
bull Process Eg Investigation (the entire lsquoexperimentalrsquo process)Eg Study (process of acquiring and treating the biological material)Eg Assay (process of performing some tests and recording the results)
31
32
33
Basic Formal Ontologya true upper level ontologyno interference with domain ontologiesno interference with physics cognitionno abstractano negative entitiesexplicit treatment of instances types and relations
34
Three dichotomies
instance vs type
continuant vs occurrent
dependent vs independent
everything in the ontology is a type
types exist in reality through their instances
35
instance vs type
experiments as instances
experiments as types
ontologies relate to types (kinds universals)
we need to keep track of instances in databases
36
BFO
ContinuantOccurrent(Process)
IndependentContinuant
DependentContinuant
37
BFO
ContinuantOccurrent(Process)
IndependentContinuant
(molecule cell organorganism)
DependentContinuant
(quality functiondisease)
Functioning Side-Effect Stochastic Process
38
BFO
ContinuantOccurrent(Process)
IndependentContinuant
(molecule cell organorganism)
PATO Functioning Side-Effect Stochastic Process
39
Unifying goal integration
Integrating datandash within and across these domainsndash across levels of granularityndash across different perspectives
Requiresndash Rigorous formal definitions in both ontologies
and annotation schemas
40
Some thoughts on the ontology itself
Outlinendash Definitions
bull how do we define PATO termsbull what exactly is it wersquore defining
ndash is_a hierarchybull what are the top-level distinctionsbull what are the finer grained distinctions
ndash shapes and colors
41
Itrsquos all about the definitions
OBO Foundry Principlendash Definitions should describe things in reality
not how terms are usedbull definitions should not use the word lsquodescribingrsquo
Scope of PATO = Phenotypic qualities
42
Old PATOEntity ndash Attribute ndash Value
Eye ndash Red ndash Dark
New PATOEntity ndash Quality
Eye ndash Red Eye ndash Dark Red
Dark Red is_a Red
43
What a quality is NOT
Qualities are not measurementsndash Instances of qualities exist independently of their
measurementsndash Qualities can have zero or more measurements
These are not the names of qualitiesndash percentagendash processndash abnormalndash high
44
Some examples of qualities
The particular redness of the left eye of a single individual flyndash An instance of a quality type
The color lsquoredrsquondash A quality type
Note the eye does not instantiate lsquoredrsquo
PATO represents quality types (universals)ndash PATO definitions can be used to classify quality
instances by the types they instantiate
45
the particular case ofredness (of a particularfly eye)
the type ldquoredrdquo
instantiates
an instance of an eye(in a particular fly)
the type ldquoeyerdquo
instantiates
inheresin (is aquality ofhas_bearer)
46
Qualities are dependent entities
Qualities require bearersndash Bearers can be physical objects or processes
Examplendash A shape requires a physical object to bear itndash If the physical object ceases to exist (eg it
decomposes) then the shape ceases to exist
48
Scale Bearer Quality Definition (proposed)
Physical Continuant Mass Equivalent to the sum of the mass of the parts of the bearer (mass at the particle level is primitiveoutwith PATO)
Physical Continuant Opacity An optical quality manifest by the capacity of the bearer to block light
PhysChem Liquid Concentration A compositional relational quality manifest by the relative quantity of some chemical type contained by the bearer
Molecular Gene splicing quality manifest by the splicing processes undergone by the bearer
Cellular Cell ploidy A cellular quality manifest by the number of genomes that are part of the bearer
Cellular Cell transformative potency
A cellular quality manifest by the capacity of the bearer cell to differentiate to different cell types
Organismal Tissue tone
Organismal Organism reproductive quality
49
How many types of shape are there
notched T-shaped Y-shaped branched unbranched antrose retrose curled curved wiggly squiggly round flat square oblong elliptical ovoid cuboid spherical egg-shaped rod-shaped heart-shaped hellip
How do we define them
How do we compare them
Shapes cannot be organized in a linear scale
Compare problem of classifying RNA structures
50
Standard case monadic qualitiesExamples
ndash E=kidney Q=hypertrophiedndash autodef a kidney which is hypertrophied
We assume that there is more contextual data (not shown)ndash eg genotype environment number of organisms
in study that showed phenotype
Interpretation (with the rest of the database record)ndash all fish in this experiment with a particular
genotype had a hypertrophied kidney at some point in time
51
Who should use PATO
Originallyndash model organism mutant phenotypes
But alsondash ontology-based evolutionary systematicsndash neuroscience BIRNndash clinical uses
bull OMIMbull clinical records (clinical manifestations)bull drug effects chemical effects
ndash to define terms in other ontologiesbull eg diploid cell invasive tumor engineered gene
condensed chromosome
- The Ontology of Experiments + PATO
- Plan
- EXPO
- Slide 4
- EXPO Formalisation of Science
- Slide 6
- Slide 7
- Slide 8
- Suggested Upper Merged Ontology
- SUMO top level
- Suggested Upper Merged Ontology
- SUMO Structure
- SUMO+Domain Ontology
- Slide 14
- Slide 15
- advantages of SUMO
- problems with SUMO as Upper-Level
- Slide 18
- Slide 19
- Slide 20
- Slide 21
- OBI
- Overview of the Ontology of Biomedical Investigations
- OBI neacutee FuGO
- Motivation for OBI
- Emerging FuGO Design Principles
- OBI Collaborating Communities
- Slide 28
- Slide 29
- FuGO - Top Level Universals
- Slide 31
- Slide 32
- Basic Formal Ontology
- Three dichotomies
- instance vs type
- BFO
- Slide 37
- Slide 38
- Unifying goal integration
- Some thoughts on the ontology itself
- Itrsquos all about the definitions
- Old PATO Entity ndash Attribute ndash Value Eye ndash Red ndash Dark
- What a quality is NOT
- Some examples of qualities
- Slide 45
- Qualities are dependent entities
- Slide 48
- How many types of shape are there
- Standard case monadic qualities
- Who should use PATO
-
3
EXPO
The Ontology of Experiments
L Soldatova R KingDepartment of Computer Science
The University of Wales Aberystwyth
4
EXPO
controlled vocabularymeta-modeltheory of contentknowledge management10487081048708 knowledge systematization10487081048708 knowledge sharing10487081048708 knowledge treatment10487081048708 knowledge reusabilitydata integration
5
EXPO Formalisation of Science
The goal of science is to increase our knowledge of the natural world through the performance of experiments
This knowledge should ideally be expressed in a formal logical language
Formal languages promote semantic clarity which in turn supports the free exchange of scientific knowledge and simplifies scientific reasoning
6
7
8
9
Suggested Upper Merged Ontology
Adam Peaseapeasearticulatesoftwarecomhttpwwwarticulatesoftwarecom
10
SUMO top levelEntity
ndash Physical bull Object
ndash SelfConnectedObject raquo Substance raquo CorpuscularObject raquo Food
ndash Region ndash Collection ndash Agent
bull Process ndash Abstract
bull SetOrClass bull Relation bull Quantity
ndash Number ndash PhysicalQuantity
bull Attribute bull Proposition
11
Suggested Upper Merged Ontology
1000 terms 4000 axioms 750 rules
Associated domain ontologies totalling 20000 terms and 60000 axioms
[includes ontology of boundaries from BS]
12
SUMO Structure
Structural Ontology
Base Ontology
SetClass Theory Numeric Temporal Mereotopology
Graph Measure Processes Objects
Qualities
13
SUMO+Domain OntologyStructuralOntology
BaseOntology
SetClassTheory
Numeric Temporal Mereotopology
Graph Measure Processes Objects
Qualities
SUMO
Mid-Level
Military
Geography
Elements
Terrorist Attack Types
Communications
People
TransnationalIssues Financial
Ontology
TerroristEconomy
NAICSTerroristAttacks
hellip
FranceAfghanistan
UnitedStates
DistributedComputing
BiologicalViruses
WMD
ECommerceServices
Government
Transportation
WorldAirports
Total Terms Total Axioms Rules
20399 67108 2500
14
entity physical object process dual object process intentional process intentional psychological process recreation or exercise organizational process guiding keeping maintaining repairing poking content development making constructing manufacture publication cooking searching social interaction maneuver motion internal change shape change abstract
15
corpuscular object =defA SelfConnectedObject whose parts have properties that are not shared by the whole
Subclass(es)organic object artifact
Coordinate term(s)content bearing object food substance
Axiom corpuscular object is disjoint from substance
substance =defAn Object in which every part is similar to every other in every relevant respect
16
advantages of SUMO
clear logical infrastructure FOL (too expressive for decidability more intuitive (human friendly) than eg OWL)
much more coherent than eg CYC upper level
much more coherent than the upper level hard wired into OWL-DL (and a fortiori into OWL-FULL)
FOL
17
problems with SUMO as Upper-Levelit contains its own tiny biology (protein
crustacean fruit-Or-vegetable )
it is overwhelmingly an ontology for abstract entities (sets functions in the mathematical sense )
no clear treatment of relations between instances vs relations between types
[all of these problems can be fixed]
18EXPO Experiment Ontology
19
representational style part_of experimental hypothesisexperimental actions part_of experimental design
20equipment part_of experimental design(confuses object with specification)
21
22
OBI
The Ontology of Biomedical Investigations
grew out of FuGE FuGO MGED PSI development activities
23
Overview of the Ontology of Biomedical Investigations
with thanks to Trish Whetzel (FuGO Working Group)
24
OBI neacutee FuGOPurpose
Provide a resource for the unambiguous description of the components of biomedical investigations such as the design protocols and instrumentation material data and types of analysis and statistical tools applied to the data NOT designed to model biology
Enables consistent annotation of data across different
technological and biological domains powerful queries semantically-driven data integration
25
Motivation for OBI
Standardization efforts in biological and technological domains Standard syntax - Data exchange formats
To provide a mechanism for software interoperability eg FuGE Object Model
Standard semantics - Controlled vocabularies or ontology Centralize commonalities for annotation term
needs across domains to describe an investigationstudyexperiment eg FuGO
26
Emerging FuGO Design Principles
OBO Foundry ontology utilize ontology best practices Inherit top level classes from an Upper Level ontology Use of the Relation Ontology Follow additional OBO Foundry principles Facilitates interoperability with other OBO Foundry
ontologiesOpen source approach
ProteacutegeacuteOWL Weekly conference calls Shared environment using Sourceforge (SF) and SF
mailing lists
27
OBI Collaborating CommunitiesCrop sciences Generation Challenge Programme (GCP)Environmental genomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiGenomic Standards Consortium (GSC)
wwwgenomicscehacukgenomecatalogueHUPO Proteomics Standards Initiative (PSI) psidevsourceforgenetImmunology Database and Analysis Portal wwwimmportorgImmune Epitope Database and Analysis Resource (IEDB)
httpwwwimmuneepitopeorghomedoInternational Society for Analytical Cytology httpwwwisac-netorgMetabolomics Standards Initiative (MSI) Neurogenetics Biomedical Informatics Research Network (BIRN)Nutrigenomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiPolymorphismToxicogenomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiTranscriptomics MGED Ontology Group
28
29
30
FuGO - Top Level Universals Continuant an entity that endureremains the same through time
bull Dependent Continuant depend on another entityEg Environment (depend on the set of ranges of conditions eg geographic location)
Eg Characteristics (entity that can be measured eg temperature unit)
- Realizable an entity that is realizable through a process (executedrun)Eg Software (a set of machine instructions)
Eg Design (the plan that can be realized in a process)
Eg Role (the part played by an entity within the context of a process)
bull Independent Continuant stands on its ownEg All physical entity (instrument technology platform document etc)
Eg Biological material (organism population etc)
Occurrent an entity that occursunfold in timebull Eg Temporal Regions Spatio-Temporal Regions (single actions or Event)
bull Process Eg Investigation (the entire lsquoexperimentalrsquo process)Eg Study (process of acquiring and treating the biological material)Eg Assay (process of performing some tests and recording the results)
31
32
33
Basic Formal Ontologya true upper level ontologyno interference with domain ontologiesno interference with physics cognitionno abstractano negative entitiesexplicit treatment of instances types and relations
34
Three dichotomies
instance vs type
continuant vs occurrent
dependent vs independent
everything in the ontology is a type
types exist in reality through their instances
35
instance vs type
experiments as instances
experiments as types
ontologies relate to types (kinds universals)
we need to keep track of instances in databases
36
BFO
ContinuantOccurrent(Process)
IndependentContinuant
DependentContinuant
37
BFO
ContinuantOccurrent(Process)
IndependentContinuant
(molecule cell organorganism)
DependentContinuant
(quality functiondisease)
Functioning Side-Effect Stochastic Process
38
BFO
ContinuantOccurrent(Process)
IndependentContinuant
(molecule cell organorganism)
PATO Functioning Side-Effect Stochastic Process
39
Unifying goal integration
Integrating datandash within and across these domainsndash across levels of granularityndash across different perspectives
Requiresndash Rigorous formal definitions in both ontologies
and annotation schemas
40
Some thoughts on the ontology itself
Outlinendash Definitions
bull how do we define PATO termsbull what exactly is it wersquore defining
ndash is_a hierarchybull what are the top-level distinctionsbull what are the finer grained distinctions
ndash shapes and colors
41
Itrsquos all about the definitions
OBO Foundry Principlendash Definitions should describe things in reality
not how terms are usedbull definitions should not use the word lsquodescribingrsquo
Scope of PATO = Phenotypic qualities
42
Old PATOEntity ndash Attribute ndash Value
Eye ndash Red ndash Dark
New PATOEntity ndash Quality
Eye ndash Red Eye ndash Dark Red
Dark Red is_a Red
43
What a quality is NOT
Qualities are not measurementsndash Instances of qualities exist independently of their
measurementsndash Qualities can have zero or more measurements
These are not the names of qualitiesndash percentagendash processndash abnormalndash high
44
Some examples of qualities
The particular redness of the left eye of a single individual flyndash An instance of a quality type
The color lsquoredrsquondash A quality type
Note the eye does not instantiate lsquoredrsquo
PATO represents quality types (universals)ndash PATO definitions can be used to classify quality
instances by the types they instantiate
45
the particular case ofredness (of a particularfly eye)
the type ldquoredrdquo
instantiates
an instance of an eye(in a particular fly)
the type ldquoeyerdquo
instantiates
inheresin (is aquality ofhas_bearer)
46
Qualities are dependent entities
Qualities require bearersndash Bearers can be physical objects or processes
Examplendash A shape requires a physical object to bear itndash If the physical object ceases to exist (eg it
decomposes) then the shape ceases to exist
48
Scale Bearer Quality Definition (proposed)
Physical Continuant Mass Equivalent to the sum of the mass of the parts of the bearer (mass at the particle level is primitiveoutwith PATO)
Physical Continuant Opacity An optical quality manifest by the capacity of the bearer to block light
PhysChem Liquid Concentration A compositional relational quality manifest by the relative quantity of some chemical type contained by the bearer
Molecular Gene splicing quality manifest by the splicing processes undergone by the bearer
Cellular Cell ploidy A cellular quality manifest by the number of genomes that are part of the bearer
Cellular Cell transformative potency
A cellular quality manifest by the capacity of the bearer cell to differentiate to different cell types
Organismal Tissue tone
Organismal Organism reproductive quality
49
How many types of shape are there
notched T-shaped Y-shaped branched unbranched antrose retrose curled curved wiggly squiggly round flat square oblong elliptical ovoid cuboid spherical egg-shaped rod-shaped heart-shaped hellip
How do we define them
How do we compare them
Shapes cannot be organized in a linear scale
Compare problem of classifying RNA structures
50
Standard case monadic qualitiesExamples
ndash E=kidney Q=hypertrophiedndash autodef a kidney which is hypertrophied
We assume that there is more contextual data (not shown)ndash eg genotype environment number of organisms
in study that showed phenotype
Interpretation (with the rest of the database record)ndash all fish in this experiment with a particular
genotype had a hypertrophied kidney at some point in time
51
Who should use PATO
Originallyndash model organism mutant phenotypes
But alsondash ontology-based evolutionary systematicsndash neuroscience BIRNndash clinical uses
bull OMIMbull clinical records (clinical manifestations)bull drug effects chemical effects
ndash to define terms in other ontologiesbull eg diploid cell invasive tumor engineered gene
condensed chromosome
- The Ontology of Experiments + PATO
- Plan
- EXPO
- Slide 4
- EXPO Formalisation of Science
- Slide 6
- Slide 7
- Slide 8
- Suggested Upper Merged Ontology
- SUMO top level
- Suggested Upper Merged Ontology
- SUMO Structure
- SUMO+Domain Ontology
- Slide 14
- Slide 15
- advantages of SUMO
- problems with SUMO as Upper-Level
- Slide 18
- Slide 19
- Slide 20
- Slide 21
- OBI
- Overview of the Ontology of Biomedical Investigations
- OBI neacutee FuGO
- Motivation for OBI
- Emerging FuGO Design Principles
- OBI Collaborating Communities
- Slide 28
- Slide 29
- FuGO - Top Level Universals
- Slide 31
- Slide 32
- Basic Formal Ontology
- Three dichotomies
- instance vs type
- BFO
- Slide 37
- Slide 38
- Unifying goal integration
- Some thoughts on the ontology itself
- Itrsquos all about the definitions
- Old PATO Entity ndash Attribute ndash Value Eye ndash Red ndash Dark
- What a quality is NOT
- Some examples of qualities
- Slide 45
- Qualities are dependent entities
- Slide 48
- How many types of shape are there
- Standard case monadic qualities
- Who should use PATO
-
4
EXPO
controlled vocabularymeta-modeltheory of contentknowledge management10487081048708 knowledge systematization10487081048708 knowledge sharing10487081048708 knowledge treatment10487081048708 knowledge reusabilitydata integration
5
EXPO Formalisation of Science
The goal of science is to increase our knowledge of the natural world through the performance of experiments
This knowledge should ideally be expressed in a formal logical language
Formal languages promote semantic clarity which in turn supports the free exchange of scientific knowledge and simplifies scientific reasoning
6
7
8
9
Suggested Upper Merged Ontology
Adam Peaseapeasearticulatesoftwarecomhttpwwwarticulatesoftwarecom
10
SUMO top levelEntity
ndash Physical bull Object
ndash SelfConnectedObject raquo Substance raquo CorpuscularObject raquo Food
ndash Region ndash Collection ndash Agent
bull Process ndash Abstract
bull SetOrClass bull Relation bull Quantity
ndash Number ndash PhysicalQuantity
bull Attribute bull Proposition
11
Suggested Upper Merged Ontology
1000 terms 4000 axioms 750 rules
Associated domain ontologies totalling 20000 terms and 60000 axioms
[includes ontology of boundaries from BS]
12
SUMO Structure
Structural Ontology
Base Ontology
SetClass Theory Numeric Temporal Mereotopology
Graph Measure Processes Objects
Qualities
13
SUMO+Domain OntologyStructuralOntology
BaseOntology
SetClassTheory
Numeric Temporal Mereotopology
Graph Measure Processes Objects
Qualities
SUMO
Mid-Level
Military
Geography
Elements
Terrorist Attack Types
Communications
People
TransnationalIssues Financial
Ontology
TerroristEconomy
NAICSTerroristAttacks
hellip
FranceAfghanistan
UnitedStates
DistributedComputing
BiologicalViruses
WMD
ECommerceServices
Government
Transportation
WorldAirports
Total Terms Total Axioms Rules
20399 67108 2500
14
entity physical object process dual object process intentional process intentional psychological process recreation or exercise organizational process guiding keeping maintaining repairing poking content development making constructing manufacture publication cooking searching social interaction maneuver motion internal change shape change abstract
15
corpuscular object =defA SelfConnectedObject whose parts have properties that are not shared by the whole
Subclass(es)organic object artifact
Coordinate term(s)content bearing object food substance
Axiom corpuscular object is disjoint from substance
substance =defAn Object in which every part is similar to every other in every relevant respect
16
advantages of SUMO
clear logical infrastructure FOL (too expressive for decidability more intuitive (human friendly) than eg OWL)
much more coherent than eg CYC upper level
much more coherent than the upper level hard wired into OWL-DL (and a fortiori into OWL-FULL)
FOL
17
problems with SUMO as Upper-Levelit contains its own tiny biology (protein
crustacean fruit-Or-vegetable )
it is overwhelmingly an ontology for abstract entities (sets functions in the mathematical sense )
no clear treatment of relations between instances vs relations between types
[all of these problems can be fixed]
18EXPO Experiment Ontology
19
representational style part_of experimental hypothesisexperimental actions part_of experimental design
20equipment part_of experimental design(confuses object with specification)
21
22
OBI
The Ontology of Biomedical Investigations
grew out of FuGE FuGO MGED PSI development activities
23
Overview of the Ontology of Biomedical Investigations
with thanks to Trish Whetzel (FuGO Working Group)
24
OBI neacutee FuGOPurpose
Provide a resource for the unambiguous description of the components of biomedical investigations such as the design protocols and instrumentation material data and types of analysis and statistical tools applied to the data NOT designed to model biology
Enables consistent annotation of data across different
technological and biological domains powerful queries semantically-driven data integration
25
Motivation for OBI
Standardization efforts in biological and technological domains Standard syntax - Data exchange formats
To provide a mechanism for software interoperability eg FuGE Object Model
Standard semantics - Controlled vocabularies or ontology Centralize commonalities for annotation term
needs across domains to describe an investigationstudyexperiment eg FuGO
26
Emerging FuGO Design Principles
OBO Foundry ontology utilize ontology best practices Inherit top level classes from an Upper Level ontology Use of the Relation Ontology Follow additional OBO Foundry principles Facilitates interoperability with other OBO Foundry
ontologiesOpen source approach
ProteacutegeacuteOWL Weekly conference calls Shared environment using Sourceforge (SF) and SF
mailing lists
27
OBI Collaborating CommunitiesCrop sciences Generation Challenge Programme (GCP)Environmental genomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiGenomic Standards Consortium (GSC)
wwwgenomicscehacukgenomecatalogueHUPO Proteomics Standards Initiative (PSI) psidevsourceforgenetImmunology Database and Analysis Portal wwwimmportorgImmune Epitope Database and Analysis Resource (IEDB)
httpwwwimmuneepitopeorghomedoInternational Society for Analytical Cytology httpwwwisac-netorgMetabolomics Standards Initiative (MSI) Neurogenetics Biomedical Informatics Research Network (BIRN)Nutrigenomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiPolymorphismToxicogenomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiTranscriptomics MGED Ontology Group
28
29
30
FuGO - Top Level Universals Continuant an entity that endureremains the same through time
bull Dependent Continuant depend on another entityEg Environment (depend on the set of ranges of conditions eg geographic location)
Eg Characteristics (entity that can be measured eg temperature unit)
- Realizable an entity that is realizable through a process (executedrun)Eg Software (a set of machine instructions)
Eg Design (the plan that can be realized in a process)
Eg Role (the part played by an entity within the context of a process)
bull Independent Continuant stands on its ownEg All physical entity (instrument technology platform document etc)
Eg Biological material (organism population etc)
Occurrent an entity that occursunfold in timebull Eg Temporal Regions Spatio-Temporal Regions (single actions or Event)
bull Process Eg Investigation (the entire lsquoexperimentalrsquo process)Eg Study (process of acquiring and treating the biological material)Eg Assay (process of performing some tests and recording the results)
31
32
33
Basic Formal Ontologya true upper level ontologyno interference with domain ontologiesno interference with physics cognitionno abstractano negative entitiesexplicit treatment of instances types and relations
34
Three dichotomies
instance vs type
continuant vs occurrent
dependent vs independent
everything in the ontology is a type
types exist in reality through their instances
35
instance vs type
experiments as instances
experiments as types
ontologies relate to types (kinds universals)
we need to keep track of instances in databases
36
BFO
ContinuantOccurrent(Process)
IndependentContinuant
DependentContinuant
37
BFO
ContinuantOccurrent(Process)
IndependentContinuant
(molecule cell organorganism)
DependentContinuant
(quality functiondisease)
Functioning Side-Effect Stochastic Process
38
BFO
ContinuantOccurrent(Process)
IndependentContinuant
(molecule cell organorganism)
PATO Functioning Side-Effect Stochastic Process
39
Unifying goal integration
Integrating datandash within and across these domainsndash across levels of granularityndash across different perspectives
Requiresndash Rigorous formal definitions in both ontologies
and annotation schemas
40
Some thoughts on the ontology itself
Outlinendash Definitions
bull how do we define PATO termsbull what exactly is it wersquore defining
ndash is_a hierarchybull what are the top-level distinctionsbull what are the finer grained distinctions
ndash shapes and colors
41
Itrsquos all about the definitions
OBO Foundry Principlendash Definitions should describe things in reality
not how terms are usedbull definitions should not use the word lsquodescribingrsquo
Scope of PATO = Phenotypic qualities
42
Old PATOEntity ndash Attribute ndash Value
Eye ndash Red ndash Dark
New PATOEntity ndash Quality
Eye ndash Red Eye ndash Dark Red
Dark Red is_a Red
43
What a quality is NOT
Qualities are not measurementsndash Instances of qualities exist independently of their
measurementsndash Qualities can have zero or more measurements
These are not the names of qualitiesndash percentagendash processndash abnormalndash high
44
Some examples of qualities
The particular redness of the left eye of a single individual flyndash An instance of a quality type
The color lsquoredrsquondash A quality type
Note the eye does not instantiate lsquoredrsquo
PATO represents quality types (universals)ndash PATO definitions can be used to classify quality
instances by the types they instantiate
45
the particular case ofredness (of a particularfly eye)
the type ldquoredrdquo
instantiates
an instance of an eye(in a particular fly)
the type ldquoeyerdquo
instantiates
inheresin (is aquality ofhas_bearer)
46
Qualities are dependent entities
Qualities require bearersndash Bearers can be physical objects or processes
Examplendash A shape requires a physical object to bear itndash If the physical object ceases to exist (eg it
decomposes) then the shape ceases to exist
48
Scale Bearer Quality Definition (proposed)
Physical Continuant Mass Equivalent to the sum of the mass of the parts of the bearer (mass at the particle level is primitiveoutwith PATO)
Physical Continuant Opacity An optical quality manifest by the capacity of the bearer to block light
PhysChem Liquid Concentration A compositional relational quality manifest by the relative quantity of some chemical type contained by the bearer
Molecular Gene splicing quality manifest by the splicing processes undergone by the bearer
Cellular Cell ploidy A cellular quality manifest by the number of genomes that are part of the bearer
Cellular Cell transformative potency
A cellular quality manifest by the capacity of the bearer cell to differentiate to different cell types
Organismal Tissue tone
Organismal Organism reproductive quality
49
How many types of shape are there
notched T-shaped Y-shaped branched unbranched antrose retrose curled curved wiggly squiggly round flat square oblong elliptical ovoid cuboid spherical egg-shaped rod-shaped heart-shaped hellip
How do we define them
How do we compare them
Shapes cannot be organized in a linear scale
Compare problem of classifying RNA structures
50
Standard case monadic qualitiesExamples
ndash E=kidney Q=hypertrophiedndash autodef a kidney which is hypertrophied
We assume that there is more contextual data (not shown)ndash eg genotype environment number of organisms
in study that showed phenotype
Interpretation (with the rest of the database record)ndash all fish in this experiment with a particular
genotype had a hypertrophied kidney at some point in time
51
Who should use PATO
Originallyndash model organism mutant phenotypes
But alsondash ontology-based evolutionary systematicsndash neuroscience BIRNndash clinical uses
bull OMIMbull clinical records (clinical manifestations)bull drug effects chemical effects
ndash to define terms in other ontologiesbull eg diploid cell invasive tumor engineered gene
condensed chromosome
- The Ontology of Experiments + PATO
- Plan
- EXPO
- Slide 4
- EXPO Formalisation of Science
- Slide 6
- Slide 7
- Slide 8
- Suggested Upper Merged Ontology
- SUMO top level
- Suggested Upper Merged Ontology
- SUMO Structure
- SUMO+Domain Ontology
- Slide 14
- Slide 15
- advantages of SUMO
- problems with SUMO as Upper-Level
- Slide 18
- Slide 19
- Slide 20
- Slide 21
- OBI
- Overview of the Ontology of Biomedical Investigations
- OBI neacutee FuGO
- Motivation for OBI
- Emerging FuGO Design Principles
- OBI Collaborating Communities
- Slide 28
- Slide 29
- FuGO - Top Level Universals
- Slide 31
- Slide 32
- Basic Formal Ontology
- Three dichotomies
- instance vs type
- BFO
- Slide 37
- Slide 38
- Unifying goal integration
- Some thoughts on the ontology itself
- Itrsquos all about the definitions
- Old PATO Entity ndash Attribute ndash Value Eye ndash Red ndash Dark
- What a quality is NOT
- Some examples of qualities
- Slide 45
- Qualities are dependent entities
- Slide 48
- How many types of shape are there
- Standard case monadic qualities
- Who should use PATO
-
5
EXPO Formalisation of Science
The goal of science is to increase our knowledge of the natural world through the performance of experiments
This knowledge should ideally be expressed in a formal logical language
Formal languages promote semantic clarity which in turn supports the free exchange of scientific knowledge and simplifies scientific reasoning
6
7
8
9
Suggested Upper Merged Ontology
Adam Peaseapeasearticulatesoftwarecomhttpwwwarticulatesoftwarecom
10
SUMO top levelEntity
ndash Physical bull Object
ndash SelfConnectedObject raquo Substance raquo CorpuscularObject raquo Food
ndash Region ndash Collection ndash Agent
bull Process ndash Abstract
bull SetOrClass bull Relation bull Quantity
ndash Number ndash PhysicalQuantity
bull Attribute bull Proposition
11
Suggested Upper Merged Ontology
1000 terms 4000 axioms 750 rules
Associated domain ontologies totalling 20000 terms and 60000 axioms
[includes ontology of boundaries from BS]
12
SUMO Structure
Structural Ontology
Base Ontology
SetClass Theory Numeric Temporal Mereotopology
Graph Measure Processes Objects
Qualities
13
SUMO+Domain OntologyStructuralOntology
BaseOntology
SetClassTheory
Numeric Temporal Mereotopology
Graph Measure Processes Objects
Qualities
SUMO
Mid-Level
Military
Geography
Elements
Terrorist Attack Types
Communications
People
TransnationalIssues Financial
Ontology
TerroristEconomy
NAICSTerroristAttacks
hellip
FranceAfghanistan
UnitedStates
DistributedComputing
BiologicalViruses
WMD
ECommerceServices
Government
Transportation
WorldAirports
Total Terms Total Axioms Rules
20399 67108 2500
14
entity physical object process dual object process intentional process intentional psychological process recreation or exercise organizational process guiding keeping maintaining repairing poking content development making constructing manufacture publication cooking searching social interaction maneuver motion internal change shape change abstract
15
corpuscular object =defA SelfConnectedObject whose parts have properties that are not shared by the whole
Subclass(es)organic object artifact
Coordinate term(s)content bearing object food substance
Axiom corpuscular object is disjoint from substance
substance =defAn Object in which every part is similar to every other in every relevant respect
16
advantages of SUMO
clear logical infrastructure FOL (too expressive for decidability more intuitive (human friendly) than eg OWL)
much more coherent than eg CYC upper level
much more coherent than the upper level hard wired into OWL-DL (and a fortiori into OWL-FULL)
FOL
17
problems with SUMO as Upper-Levelit contains its own tiny biology (protein
crustacean fruit-Or-vegetable )
it is overwhelmingly an ontology for abstract entities (sets functions in the mathematical sense )
no clear treatment of relations between instances vs relations between types
[all of these problems can be fixed]
18EXPO Experiment Ontology
19
representational style part_of experimental hypothesisexperimental actions part_of experimental design
20equipment part_of experimental design(confuses object with specification)
21
22
OBI
The Ontology of Biomedical Investigations
grew out of FuGE FuGO MGED PSI development activities
23
Overview of the Ontology of Biomedical Investigations
with thanks to Trish Whetzel (FuGO Working Group)
24
OBI neacutee FuGOPurpose
Provide a resource for the unambiguous description of the components of biomedical investigations such as the design protocols and instrumentation material data and types of analysis and statistical tools applied to the data NOT designed to model biology
Enables consistent annotation of data across different
technological and biological domains powerful queries semantically-driven data integration
25
Motivation for OBI
Standardization efforts in biological and technological domains Standard syntax - Data exchange formats
To provide a mechanism for software interoperability eg FuGE Object Model
Standard semantics - Controlled vocabularies or ontology Centralize commonalities for annotation term
needs across domains to describe an investigationstudyexperiment eg FuGO
26
Emerging FuGO Design Principles
OBO Foundry ontology utilize ontology best practices Inherit top level classes from an Upper Level ontology Use of the Relation Ontology Follow additional OBO Foundry principles Facilitates interoperability with other OBO Foundry
ontologiesOpen source approach
ProteacutegeacuteOWL Weekly conference calls Shared environment using Sourceforge (SF) and SF
mailing lists
27
OBI Collaborating CommunitiesCrop sciences Generation Challenge Programme (GCP)Environmental genomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiGenomic Standards Consortium (GSC)
wwwgenomicscehacukgenomecatalogueHUPO Proteomics Standards Initiative (PSI) psidevsourceforgenetImmunology Database and Analysis Portal wwwimmportorgImmune Epitope Database and Analysis Resource (IEDB)
httpwwwimmuneepitopeorghomedoInternational Society for Analytical Cytology httpwwwisac-netorgMetabolomics Standards Initiative (MSI) Neurogenetics Biomedical Informatics Research Network (BIRN)Nutrigenomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiPolymorphismToxicogenomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiTranscriptomics MGED Ontology Group
28
29
30
FuGO - Top Level Universals Continuant an entity that endureremains the same through time
bull Dependent Continuant depend on another entityEg Environment (depend on the set of ranges of conditions eg geographic location)
Eg Characteristics (entity that can be measured eg temperature unit)
- Realizable an entity that is realizable through a process (executedrun)Eg Software (a set of machine instructions)
Eg Design (the plan that can be realized in a process)
Eg Role (the part played by an entity within the context of a process)
bull Independent Continuant stands on its ownEg All physical entity (instrument technology platform document etc)
Eg Biological material (organism population etc)
Occurrent an entity that occursunfold in timebull Eg Temporal Regions Spatio-Temporal Regions (single actions or Event)
bull Process Eg Investigation (the entire lsquoexperimentalrsquo process)Eg Study (process of acquiring and treating the biological material)Eg Assay (process of performing some tests and recording the results)
31
32
33
Basic Formal Ontologya true upper level ontologyno interference with domain ontologiesno interference with physics cognitionno abstractano negative entitiesexplicit treatment of instances types and relations
34
Three dichotomies
instance vs type
continuant vs occurrent
dependent vs independent
everything in the ontology is a type
types exist in reality through their instances
35
instance vs type
experiments as instances
experiments as types
ontologies relate to types (kinds universals)
we need to keep track of instances in databases
36
BFO
ContinuantOccurrent(Process)
IndependentContinuant
DependentContinuant
37
BFO
ContinuantOccurrent(Process)
IndependentContinuant
(molecule cell organorganism)
DependentContinuant
(quality functiondisease)
Functioning Side-Effect Stochastic Process
38
BFO
ContinuantOccurrent(Process)
IndependentContinuant
(molecule cell organorganism)
PATO Functioning Side-Effect Stochastic Process
39
Unifying goal integration
Integrating datandash within and across these domainsndash across levels of granularityndash across different perspectives
Requiresndash Rigorous formal definitions in both ontologies
and annotation schemas
40
Some thoughts on the ontology itself
Outlinendash Definitions
bull how do we define PATO termsbull what exactly is it wersquore defining
ndash is_a hierarchybull what are the top-level distinctionsbull what are the finer grained distinctions
ndash shapes and colors
41
Itrsquos all about the definitions
OBO Foundry Principlendash Definitions should describe things in reality
not how terms are usedbull definitions should not use the word lsquodescribingrsquo
Scope of PATO = Phenotypic qualities
42
Old PATOEntity ndash Attribute ndash Value
Eye ndash Red ndash Dark
New PATOEntity ndash Quality
Eye ndash Red Eye ndash Dark Red
Dark Red is_a Red
43
What a quality is NOT
Qualities are not measurementsndash Instances of qualities exist independently of their
measurementsndash Qualities can have zero or more measurements
These are not the names of qualitiesndash percentagendash processndash abnormalndash high
44
Some examples of qualities
The particular redness of the left eye of a single individual flyndash An instance of a quality type
The color lsquoredrsquondash A quality type
Note the eye does not instantiate lsquoredrsquo
PATO represents quality types (universals)ndash PATO definitions can be used to classify quality
instances by the types they instantiate
45
the particular case ofredness (of a particularfly eye)
the type ldquoredrdquo
instantiates
an instance of an eye(in a particular fly)
the type ldquoeyerdquo
instantiates
inheresin (is aquality ofhas_bearer)
46
Qualities are dependent entities
Qualities require bearersndash Bearers can be physical objects or processes
Examplendash A shape requires a physical object to bear itndash If the physical object ceases to exist (eg it
decomposes) then the shape ceases to exist
48
Scale Bearer Quality Definition (proposed)
Physical Continuant Mass Equivalent to the sum of the mass of the parts of the bearer (mass at the particle level is primitiveoutwith PATO)
Physical Continuant Opacity An optical quality manifest by the capacity of the bearer to block light
PhysChem Liquid Concentration A compositional relational quality manifest by the relative quantity of some chemical type contained by the bearer
Molecular Gene splicing quality manifest by the splicing processes undergone by the bearer
Cellular Cell ploidy A cellular quality manifest by the number of genomes that are part of the bearer
Cellular Cell transformative potency
A cellular quality manifest by the capacity of the bearer cell to differentiate to different cell types
Organismal Tissue tone
Organismal Organism reproductive quality
49
How many types of shape are there
notched T-shaped Y-shaped branched unbranched antrose retrose curled curved wiggly squiggly round flat square oblong elliptical ovoid cuboid spherical egg-shaped rod-shaped heart-shaped hellip
How do we define them
How do we compare them
Shapes cannot be organized in a linear scale
Compare problem of classifying RNA structures
50
Standard case monadic qualitiesExamples
ndash E=kidney Q=hypertrophiedndash autodef a kidney which is hypertrophied
We assume that there is more contextual data (not shown)ndash eg genotype environment number of organisms
in study that showed phenotype
Interpretation (with the rest of the database record)ndash all fish in this experiment with a particular
genotype had a hypertrophied kidney at some point in time
51
Who should use PATO
Originallyndash model organism mutant phenotypes
But alsondash ontology-based evolutionary systematicsndash neuroscience BIRNndash clinical uses
bull OMIMbull clinical records (clinical manifestations)bull drug effects chemical effects
ndash to define terms in other ontologiesbull eg diploid cell invasive tumor engineered gene
condensed chromosome
- The Ontology of Experiments + PATO
- Plan
- EXPO
- Slide 4
- EXPO Formalisation of Science
- Slide 6
- Slide 7
- Slide 8
- Suggested Upper Merged Ontology
- SUMO top level
- Suggested Upper Merged Ontology
- SUMO Structure
- SUMO+Domain Ontology
- Slide 14
- Slide 15
- advantages of SUMO
- problems with SUMO as Upper-Level
- Slide 18
- Slide 19
- Slide 20
- Slide 21
- OBI
- Overview of the Ontology of Biomedical Investigations
- OBI neacutee FuGO
- Motivation for OBI
- Emerging FuGO Design Principles
- OBI Collaborating Communities
- Slide 28
- Slide 29
- FuGO - Top Level Universals
- Slide 31
- Slide 32
- Basic Formal Ontology
- Three dichotomies
- instance vs type
- BFO
- Slide 37
- Slide 38
- Unifying goal integration
- Some thoughts on the ontology itself
- Itrsquos all about the definitions
- Old PATO Entity ndash Attribute ndash Value Eye ndash Red ndash Dark
- What a quality is NOT
- Some examples of qualities
- Slide 45
- Qualities are dependent entities
- Slide 48
- How many types of shape are there
- Standard case monadic qualities
- Who should use PATO
-
6
7
8
9
Suggested Upper Merged Ontology
Adam Peaseapeasearticulatesoftwarecomhttpwwwarticulatesoftwarecom
10
SUMO top levelEntity
ndash Physical bull Object
ndash SelfConnectedObject raquo Substance raquo CorpuscularObject raquo Food
ndash Region ndash Collection ndash Agent
bull Process ndash Abstract
bull SetOrClass bull Relation bull Quantity
ndash Number ndash PhysicalQuantity
bull Attribute bull Proposition
11
Suggested Upper Merged Ontology
1000 terms 4000 axioms 750 rules
Associated domain ontologies totalling 20000 terms and 60000 axioms
[includes ontology of boundaries from BS]
12
SUMO Structure
Structural Ontology
Base Ontology
SetClass Theory Numeric Temporal Mereotopology
Graph Measure Processes Objects
Qualities
13
SUMO+Domain OntologyStructuralOntology
BaseOntology
SetClassTheory
Numeric Temporal Mereotopology
Graph Measure Processes Objects
Qualities
SUMO
Mid-Level
Military
Geography
Elements
Terrorist Attack Types
Communications
People
TransnationalIssues Financial
Ontology
TerroristEconomy
NAICSTerroristAttacks
hellip
FranceAfghanistan
UnitedStates
DistributedComputing
BiologicalViruses
WMD
ECommerceServices
Government
Transportation
WorldAirports
Total Terms Total Axioms Rules
20399 67108 2500
14
entity physical object process dual object process intentional process intentional psychological process recreation or exercise organizational process guiding keeping maintaining repairing poking content development making constructing manufacture publication cooking searching social interaction maneuver motion internal change shape change abstract
15
corpuscular object =defA SelfConnectedObject whose parts have properties that are not shared by the whole
Subclass(es)organic object artifact
Coordinate term(s)content bearing object food substance
Axiom corpuscular object is disjoint from substance
substance =defAn Object in which every part is similar to every other in every relevant respect
16
advantages of SUMO
clear logical infrastructure FOL (too expressive for decidability more intuitive (human friendly) than eg OWL)
much more coherent than eg CYC upper level
much more coherent than the upper level hard wired into OWL-DL (and a fortiori into OWL-FULL)
FOL
17
problems with SUMO as Upper-Levelit contains its own tiny biology (protein
crustacean fruit-Or-vegetable )
it is overwhelmingly an ontology for abstract entities (sets functions in the mathematical sense )
no clear treatment of relations between instances vs relations between types
[all of these problems can be fixed]
18EXPO Experiment Ontology
19
representational style part_of experimental hypothesisexperimental actions part_of experimental design
20equipment part_of experimental design(confuses object with specification)
21
22
OBI
The Ontology of Biomedical Investigations
grew out of FuGE FuGO MGED PSI development activities
23
Overview of the Ontology of Biomedical Investigations
with thanks to Trish Whetzel (FuGO Working Group)
24
OBI neacutee FuGOPurpose
Provide a resource for the unambiguous description of the components of biomedical investigations such as the design protocols and instrumentation material data and types of analysis and statistical tools applied to the data NOT designed to model biology
Enables consistent annotation of data across different
technological and biological domains powerful queries semantically-driven data integration
25
Motivation for OBI
Standardization efforts in biological and technological domains Standard syntax - Data exchange formats
To provide a mechanism for software interoperability eg FuGE Object Model
Standard semantics - Controlled vocabularies or ontology Centralize commonalities for annotation term
needs across domains to describe an investigationstudyexperiment eg FuGO
26
Emerging FuGO Design Principles
OBO Foundry ontology utilize ontology best practices Inherit top level classes from an Upper Level ontology Use of the Relation Ontology Follow additional OBO Foundry principles Facilitates interoperability with other OBO Foundry
ontologiesOpen source approach
ProteacutegeacuteOWL Weekly conference calls Shared environment using Sourceforge (SF) and SF
mailing lists
27
OBI Collaborating CommunitiesCrop sciences Generation Challenge Programme (GCP)Environmental genomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiGenomic Standards Consortium (GSC)
wwwgenomicscehacukgenomecatalogueHUPO Proteomics Standards Initiative (PSI) psidevsourceforgenetImmunology Database and Analysis Portal wwwimmportorgImmune Epitope Database and Analysis Resource (IEDB)
httpwwwimmuneepitopeorghomedoInternational Society for Analytical Cytology httpwwwisac-netorgMetabolomics Standards Initiative (MSI) Neurogenetics Biomedical Informatics Research Network (BIRN)Nutrigenomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiPolymorphismToxicogenomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiTranscriptomics MGED Ontology Group
28
29
30
FuGO - Top Level Universals Continuant an entity that endureremains the same through time
bull Dependent Continuant depend on another entityEg Environment (depend on the set of ranges of conditions eg geographic location)
Eg Characteristics (entity that can be measured eg temperature unit)
- Realizable an entity that is realizable through a process (executedrun)Eg Software (a set of machine instructions)
Eg Design (the plan that can be realized in a process)
Eg Role (the part played by an entity within the context of a process)
bull Independent Continuant stands on its ownEg All physical entity (instrument technology platform document etc)
Eg Biological material (organism population etc)
Occurrent an entity that occursunfold in timebull Eg Temporal Regions Spatio-Temporal Regions (single actions or Event)
bull Process Eg Investigation (the entire lsquoexperimentalrsquo process)Eg Study (process of acquiring and treating the biological material)Eg Assay (process of performing some tests and recording the results)
31
32
33
Basic Formal Ontologya true upper level ontologyno interference with domain ontologiesno interference with physics cognitionno abstractano negative entitiesexplicit treatment of instances types and relations
34
Three dichotomies
instance vs type
continuant vs occurrent
dependent vs independent
everything in the ontology is a type
types exist in reality through their instances
35
instance vs type
experiments as instances
experiments as types
ontologies relate to types (kinds universals)
we need to keep track of instances in databases
36
BFO
ContinuantOccurrent(Process)
IndependentContinuant
DependentContinuant
37
BFO
ContinuantOccurrent(Process)
IndependentContinuant
(molecule cell organorganism)
DependentContinuant
(quality functiondisease)
Functioning Side-Effect Stochastic Process
38
BFO
ContinuantOccurrent(Process)
IndependentContinuant
(molecule cell organorganism)
PATO Functioning Side-Effect Stochastic Process
39
Unifying goal integration
Integrating datandash within and across these domainsndash across levels of granularityndash across different perspectives
Requiresndash Rigorous formal definitions in both ontologies
and annotation schemas
40
Some thoughts on the ontology itself
Outlinendash Definitions
bull how do we define PATO termsbull what exactly is it wersquore defining
ndash is_a hierarchybull what are the top-level distinctionsbull what are the finer grained distinctions
ndash shapes and colors
41
Itrsquos all about the definitions
OBO Foundry Principlendash Definitions should describe things in reality
not how terms are usedbull definitions should not use the word lsquodescribingrsquo
Scope of PATO = Phenotypic qualities
42
Old PATOEntity ndash Attribute ndash Value
Eye ndash Red ndash Dark
New PATOEntity ndash Quality
Eye ndash Red Eye ndash Dark Red
Dark Red is_a Red
43
What a quality is NOT
Qualities are not measurementsndash Instances of qualities exist independently of their
measurementsndash Qualities can have zero or more measurements
These are not the names of qualitiesndash percentagendash processndash abnormalndash high
44
Some examples of qualities
The particular redness of the left eye of a single individual flyndash An instance of a quality type
The color lsquoredrsquondash A quality type
Note the eye does not instantiate lsquoredrsquo
PATO represents quality types (universals)ndash PATO definitions can be used to classify quality
instances by the types they instantiate
45
the particular case ofredness (of a particularfly eye)
the type ldquoredrdquo
instantiates
an instance of an eye(in a particular fly)
the type ldquoeyerdquo
instantiates
inheresin (is aquality ofhas_bearer)
46
Qualities are dependent entities
Qualities require bearersndash Bearers can be physical objects or processes
Examplendash A shape requires a physical object to bear itndash If the physical object ceases to exist (eg it
decomposes) then the shape ceases to exist
48
Scale Bearer Quality Definition (proposed)
Physical Continuant Mass Equivalent to the sum of the mass of the parts of the bearer (mass at the particle level is primitiveoutwith PATO)
Physical Continuant Opacity An optical quality manifest by the capacity of the bearer to block light
PhysChem Liquid Concentration A compositional relational quality manifest by the relative quantity of some chemical type contained by the bearer
Molecular Gene splicing quality manifest by the splicing processes undergone by the bearer
Cellular Cell ploidy A cellular quality manifest by the number of genomes that are part of the bearer
Cellular Cell transformative potency
A cellular quality manifest by the capacity of the bearer cell to differentiate to different cell types
Organismal Tissue tone
Organismal Organism reproductive quality
49
How many types of shape are there
notched T-shaped Y-shaped branched unbranched antrose retrose curled curved wiggly squiggly round flat square oblong elliptical ovoid cuboid spherical egg-shaped rod-shaped heart-shaped hellip
How do we define them
How do we compare them
Shapes cannot be organized in a linear scale
Compare problem of classifying RNA structures
50
Standard case monadic qualitiesExamples
ndash E=kidney Q=hypertrophiedndash autodef a kidney which is hypertrophied
We assume that there is more contextual data (not shown)ndash eg genotype environment number of organisms
in study that showed phenotype
Interpretation (with the rest of the database record)ndash all fish in this experiment with a particular
genotype had a hypertrophied kidney at some point in time
51
Who should use PATO
Originallyndash model organism mutant phenotypes
But alsondash ontology-based evolutionary systematicsndash neuroscience BIRNndash clinical uses
bull OMIMbull clinical records (clinical manifestations)bull drug effects chemical effects
ndash to define terms in other ontologiesbull eg diploid cell invasive tumor engineered gene
condensed chromosome
- The Ontology of Experiments + PATO
- Plan
- EXPO
- Slide 4
- EXPO Formalisation of Science
- Slide 6
- Slide 7
- Slide 8
- Suggested Upper Merged Ontology
- SUMO top level
- Suggested Upper Merged Ontology
- SUMO Structure
- SUMO+Domain Ontology
- Slide 14
- Slide 15
- advantages of SUMO
- problems with SUMO as Upper-Level
- Slide 18
- Slide 19
- Slide 20
- Slide 21
- OBI
- Overview of the Ontology of Biomedical Investigations
- OBI neacutee FuGO
- Motivation for OBI
- Emerging FuGO Design Principles
- OBI Collaborating Communities
- Slide 28
- Slide 29
- FuGO - Top Level Universals
- Slide 31
- Slide 32
- Basic Formal Ontology
- Three dichotomies
- instance vs type
- BFO
- Slide 37
- Slide 38
- Unifying goal integration
- Some thoughts on the ontology itself
- Itrsquos all about the definitions
- Old PATO Entity ndash Attribute ndash Value Eye ndash Red ndash Dark
- What a quality is NOT
- Some examples of qualities
- Slide 45
- Qualities are dependent entities
- Slide 48
- How many types of shape are there
- Standard case monadic qualities
- Who should use PATO
-
7
8
9
Suggested Upper Merged Ontology
Adam Peaseapeasearticulatesoftwarecomhttpwwwarticulatesoftwarecom
10
SUMO top levelEntity
ndash Physical bull Object
ndash SelfConnectedObject raquo Substance raquo CorpuscularObject raquo Food
ndash Region ndash Collection ndash Agent
bull Process ndash Abstract
bull SetOrClass bull Relation bull Quantity
ndash Number ndash PhysicalQuantity
bull Attribute bull Proposition
11
Suggested Upper Merged Ontology
1000 terms 4000 axioms 750 rules
Associated domain ontologies totalling 20000 terms and 60000 axioms
[includes ontology of boundaries from BS]
12
SUMO Structure
Structural Ontology
Base Ontology
SetClass Theory Numeric Temporal Mereotopology
Graph Measure Processes Objects
Qualities
13
SUMO+Domain OntologyStructuralOntology
BaseOntology
SetClassTheory
Numeric Temporal Mereotopology
Graph Measure Processes Objects
Qualities
SUMO
Mid-Level
Military
Geography
Elements
Terrorist Attack Types
Communications
People
TransnationalIssues Financial
Ontology
TerroristEconomy
NAICSTerroristAttacks
hellip
FranceAfghanistan
UnitedStates
DistributedComputing
BiologicalViruses
WMD
ECommerceServices
Government
Transportation
WorldAirports
Total Terms Total Axioms Rules
20399 67108 2500
14
entity physical object process dual object process intentional process intentional psychological process recreation or exercise organizational process guiding keeping maintaining repairing poking content development making constructing manufacture publication cooking searching social interaction maneuver motion internal change shape change abstract
15
corpuscular object =defA SelfConnectedObject whose parts have properties that are not shared by the whole
Subclass(es)organic object artifact
Coordinate term(s)content bearing object food substance
Axiom corpuscular object is disjoint from substance
substance =defAn Object in which every part is similar to every other in every relevant respect
16
advantages of SUMO
clear logical infrastructure FOL (too expressive for decidability more intuitive (human friendly) than eg OWL)
much more coherent than eg CYC upper level
much more coherent than the upper level hard wired into OWL-DL (and a fortiori into OWL-FULL)
FOL
17
problems with SUMO as Upper-Levelit contains its own tiny biology (protein
crustacean fruit-Or-vegetable )
it is overwhelmingly an ontology for abstract entities (sets functions in the mathematical sense )
no clear treatment of relations between instances vs relations between types
[all of these problems can be fixed]
18EXPO Experiment Ontology
19
representational style part_of experimental hypothesisexperimental actions part_of experimental design
20equipment part_of experimental design(confuses object with specification)
21
22
OBI
The Ontology of Biomedical Investigations
grew out of FuGE FuGO MGED PSI development activities
23
Overview of the Ontology of Biomedical Investigations
with thanks to Trish Whetzel (FuGO Working Group)
24
OBI neacutee FuGOPurpose
Provide a resource for the unambiguous description of the components of biomedical investigations such as the design protocols and instrumentation material data and types of analysis and statistical tools applied to the data NOT designed to model biology
Enables consistent annotation of data across different
technological and biological domains powerful queries semantically-driven data integration
25
Motivation for OBI
Standardization efforts in biological and technological domains Standard syntax - Data exchange formats
To provide a mechanism for software interoperability eg FuGE Object Model
Standard semantics - Controlled vocabularies or ontology Centralize commonalities for annotation term
needs across domains to describe an investigationstudyexperiment eg FuGO
26
Emerging FuGO Design Principles
OBO Foundry ontology utilize ontology best practices Inherit top level classes from an Upper Level ontology Use of the Relation Ontology Follow additional OBO Foundry principles Facilitates interoperability with other OBO Foundry
ontologiesOpen source approach
ProteacutegeacuteOWL Weekly conference calls Shared environment using Sourceforge (SF) and SF
mailing lists
27
OBI Collaborating CommunitiesCrop sciences Generation Challenge Programme (GCP)Environmental genomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiGenomic Standards Consortium (GSC)
wwwgenomicscehacukgenomecatalogueHUPO Proteomics Standards Initiative (PSI) psidevsourceforgenetImmunology Database and Analysis Portal wwwimmportorgImmune Epitope Database and Analysis Resource (IEDB)
httpwwwimmuneepitopeorghomedoInternational Society for Analytical Cytology httpwwwisac-netorgMetabolomics Standards Initiative (MSI) Neurogenetics Biomedical Informatics Research Network (BIRN)Nutrigenomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiPolymorphismToxicogenomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiTranscriptomics MGED Ontology Group
28
29
30
FuGO - Top Level Universals Continuant an entity that endureremains the same through time
bull Dependent Continuant depend on another entityEg Environment (depend on the set of ranges of conditions eg geographic location)
Eg Characteristics (entity that can be measured eg temperature unit)
- Realizable an entity that is realizable through a process (executedrun)Eg Software (a set of machine instructions)
Eg Design (the plan that can be realized in a process)
Eg Role (the part played by an entity within the context of a process)
bull Independent Continuant stands on its ownEg All physical entity (instrument technology platform document etc)
Eg Biological material (organism population etc)
Occurrent an entity that occursunfold in timebull Eg Temporal Regions Spatio-Temporal Regions (single actions or Event)
bull Process Eg Investigation (the entire lsquoexperimentalrsquo process)Eg Study (process of acquiring and treating the biological material)Eg Assay (process of performing some tests and recording the results)
31
32
33
Basic Formal Ontologya true upper level ontologyno interference with domain ontologiesno interference with physics cognitionno abstractano negative entitiesexplicit treatment of instances types and relations
34
Three dichotomies
instance vs type
continuant vs occurrent
dependent vs independent
everything in the ontology is a type
types exist in reality through their instances
35
instance vs type
experiments as instances
experiments as types
ontologies relate to types (kinds universals)
we need to keep track of instances in databases
36
BFO
ContinuantOccurrent(Process)
IndependentContinuant
DependentContinuant
37
BFO
ContinuantOccurrent(Process)
IndependentContinuant
(molecule cell organorganism)
DependentContinuant
(quality functiondisease)
Functioning Side-Effect Stochastic Process
38
BFO
ContinuantOccurrent(Process)
IndependentContinuant
(molecule cell organorganism)
PATO Functioning Side-Effect Stochastic Process
39
Unifying goal integration
Integrating datandash within and across these domainsndash across levels of granularityndash across different perspectives
Requiresndash Rigorous formal definitions in both ontologies
and annotation schemas
40
Some thoughts on the ontology itself
Outlinendash Definitions
bull how do we define PATO termsbull what exactly is it wersquore defining
ndash is_a hierarchybull what are the top-level distinctionsbull what are the finer grained distinctions
ndash shapes and colors
41
Itrsquos all about the definitions
OBO Foundry Principlendash Definitions should describe things in reality
not how terms are usedbull definitions should not use the word lsquodescribingrsquo
Scope of PATO = Phenotypic qualities
42
Old PATOEntity ndash Attribute ndash Value
Eye ndash Red ndash Dark
New PATOEntity ndash Quality
Eye ndash Red Eye ndash Dark Red
Dark Red is_a Red
43
What a quality is NOT
Qualities are not measurementsndash Instances of qualities exist independently of their
measurementsndash Qualities can have zero or more measurements
These are not the names of qualitiesndash percentagendash processndash abnormalndash high
44
Some examples of qualities
The particular redness of the left eye of a single individual flyndash An instance of a quality type
The color lsquoredrsquondash A quality type
Note the eye does not instantiate lsquoredrsquo
PATO represents quality types (universals)ndash PATO definitions can be used to classify quality
instances by the types they instantiate
45
the particular case ofredness (of a particularfly eye)
the type ldquoredrdquo
instantiates
an instance of an eye(in a particular fly)
the type ldquoeyerdquo
instantiates
inheresin (is aquality ofhas_bearer)
46
Qualities are dependent entities
Qualities require bearersndash Bearers can be physical objects or processes
Examplendash A shape requires a physical object to bear itndash If the physical object ceases to exist (eg it
decomposes) then the shape ceases to exist
48
Scale Bearer Quality Definition (proposed)
Physical Continuant Mass Equivalent to the sum of the mass of the parts of the bearer (mass at the particle level is primitiveoutwith PATO)
Physical Continuant Opacity An optical quality manifest by the capacity of the bearer to block light
PhysChem Liquid Concentration A compositional relational quality manifest by the relative quantity of some chemical type contained by the bearer
Molecular Gene splicing quality manifest by the splicing processes undergone by the bearer
Cellular Cell ploidy A cellular quality manifest by the number of genomes that are part of the bearer
Cellular Cell transformative potency
A cellular quality manifest by the capacity of the bearer cell to differentiate to different cell types
Organismal Tissue tone
Organismal Organism reproductive quality
49
How many types of shape are there
notched T-shaped Y-shaped branched unbranched antrose retrose curled curved wiggly squiggly round flat square oblong elliptical ovoid cuboid spherical egg-shaped rod-shaped heart-shaped hellip
How do we define them
How do we compare them
Shapes cannot be organized in a linear scale
Compare problem of classifying RNA structures
50
Standard case monadic qualitiesExamples
ndash E=kidney Q=hypertrophiedndash autodef a kidney which is hypertrophied
We assume that there is more contextual data (not shown)ndash eg genotype environment number of organisms
in study that showed phenotype
Interpretation (with the rest of the database record)ndash all fish in this experiment with a particular
genotype had a hypertrophied kidney at some point in time
51
Who should use PATO
Originallyndash model organism mutant phenotypes
But alsondash ontology-based evolutionary systematicsndash neuroscience BIRNndash clinical uses
bull OMIMbull clinical records (clinical manifestations)bull drug effects chemical effects
ndash to define terms in other ontologiesbull eg diploid cell invasive tumor engineered gene
condensed chromosome
- The Ontology of Experiments + PATO
- Plan
- EXPO
- Slide 4
- EXPO Formalisation of Science
- Slide 6
- Slide 7
- Slide 8
- Suggested Upper Merged Ontology
- SUMO top level
- Suggested Upper Merged Ontology
- SUMO Structure
- SUMO+Domain Ontology
- Slide 14
- Slide 15
- advantages of SUMO
- problems with SUMO as Upper-Level
- Slide 18
- Slide 19
- Slide 20
- Slide 21
- OBI
- Overview of the Ontology of Biomedical Investigations
- OBI neacutee FuGO
- Motivation for OBI
- Emerging FuGO Design Principles
- OBI Collaborating Communities
- Slide 28
- Slide 29
- FuGO - Top Level Universals
- Slide 31
- Slide 32
- Basic Formal Ontology
- Three dichotomies
- instance vs type
- BFO
- Slide 37
- Slide 38
- Unifying goal integration
- Some thoughts on the ontology itself
- Itrsquos all about the definitions
- Old PATO Entity ndash Attribute ndash Value Eye ndash Red ndash Dark
- What a quality is NOT
- Some examples of qualities
- Slide 45
- Qualities are dependent entities
- Slide 48
- How many types of shape are there
- Standard case monadic qualities
- Who should use PATO
-
8
9
Suggested Upper Merged Ontology
Adam Peaseapeasearticulatesoftwarecomhttpwwwarticulatesoftwarecom
10
SUMO top levelEntity
ndash Physical bull Object
ndash SelfConnectedObject raquo Substance raquo CorpuscularObject raquo Food
ndash Region ndash Collection ndash Agent
bull Process ndash Abstract
bull SetOrClass bull Relation bull Quantity
ndash Number ndash PhysicalQuantity
bull Attribute bull Proposition
11
Suggested Upper Merged Ontology
1000 terms 4000 axioms 750 rules
Associated domain ontologies totalling 20000 terms and 60000 axioms
[includes ontology of boundaries from BS]
12
SUMO Structure
Structural Ontology
Base Ontology
SetClass Theory Numeric Temporal Mereotopology
Graph Measure Processes Objects
Qualities
13
SUMO+Domain OntologyStructuralOntology
BaseOntology
SetClassTheory
Numeric Temporal Mereotopology
Graph Measure Processes Objects
Qualities
SUMO
Mid-Level
Military
Geography
Elements
Terrorist Attack Types
Communications
People
TransnationalIssues Financial
Ontology
TerroristEconomy
NAICSTerroristAttacks
hellip
FranceAfghanistan
UnitedStates
DistributedComputing
BiologicalViruses
WMD
ECommerceServices
Government
Transportation
WorldAirports
Total Terms Total Axioms Rules
20399 67108 2500
14
entity physical object process dual object process intentional process intentional psychological process recreation or exercise organizational process guiding keeping maintaining repairing poking content development making constructing manufacture publication cooking searching social interaction maneuver motion internal change shape change abstract
15
corpuscular object =defA SelfConnectedObject whose parts have properties that are not shared by the whole
Subclass(es)organic object artifact
Coordinate term(s)content bearing object food substance
Axiom corpuscular object is disjoint from substance
substance =defAn Object in which every part is similar to every other in every relevant respect
16
advantages of SUMO
clear logical infrastructure FOL (too expressive for decidability more intuitive (human friendly) than eg OWL)
much more coherent than eg CYC upper level
much more coherent than the upper level hard wired into OWL-DL (and a fortiori into OWL-FULL)
FOL
17
problems with SUMO as Upper-Levelit contains its own tiny biology (protein
crustacean fruit-Or-vegetable )
it is overwhelmingly an ontology for abstract entities (sets functions in the mathematical sense )
no clear treatment of relations between instances vs relations between types
[all of these problems can be fixed]
18EXPO Experiment Ontology
19
representational style part_of experimental hypothesisexperimental actions part_of experimental design
20equipment part_of experimental design(confuses object with specification)
21
22
OBI
The Ontology of Biomedical Investigations
grew out of FuGE FuGO MGED PSI development activities
23
Overview of the Ontology of Biomedical Investigations
with thanks to Trish Whetzel (FuGO Working Group)
24
OBI neacutee FuGOPurpose
Provide a resource for the unambiguous description of the components of biomedical investigations such as the design protocols and instrumentation material data and types of analysis and statistical tools applied to the data NOT designed to model biology
Enables consistent annotation of data across different
technological and biological domains powerful queries semantically-driven data integration
25
Motivation for OBI
Standardization efforts in biological and technological domains Standard syntax - Data exchange formats
To provide a mechanism for software interoperability eg FuGE Object Model
Standard semantics - Controlled vocabularies or ontology Centralize commonalities for annotation term
needs across domains to describe an investigationstudyexperiment eg FuGO
26
Emerging FuGO Design Principles
OBO Foundry ontology utilize ontology best practices Inherit top level classes from an Upper Level ontology Use of the Relation Ontology Follow additional OBO Foundry principles Facilitates interoperability with other OBO Foundry
ontologiesOpen source approach
ProteacutegeacuteOWL Weekly conference calls Shared environment using Sourceforge (SF) and SF
mailing lists
27
OBI Collaborating CommunitiesCrop sciences Generation Challenge Programme (GCP)Environmental genomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiGenomic Standards Consortium (GSC)
wwwgenomicscehacukgenomecatalogueHUPO Proteomics Standards Initiative (PSI) psidevsourceforgenetImmunology Database and Analysis Portal wwwimmportorgImmune Epitope Database and Analysis Resource (IEDB)
httpwwwimmuneepitopeorghomedoInternational Society for Analytical Cytology httpwwwisac-netorgMetabolomics Standards Initiative (MSI) Neurogenetics Biomedical Informatics Research Network (BIRN)Nutrigenomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiPolymorphismToxicogenomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiTranscriptomics MGED Ontology Group
28
29
30
FuGO - Top Level Universals Continuant an entity that endureremains the same through time
bull Dependent Continuant depend on another entityEg Environment (depend on the set of ranges of conditions eg geographic location)
Eg Characteristics (entity that can be measured eg temperature unit)
- Realizable an entity that is realizable through a process (executedrun)Eg Software (a set of machine instructions)
Eg Design (the plan that can be realized in a process)
Eg Role (the part played by an entity within the context of a process)
bull Independent Continuant stands on its ownEg All physical entity (instrument technology platform document etc)
Eg Biological material (organism population etc)
Occurrent an entity that occursunfold in timebull Eg Temporal Regions Spatio-Temporal Regions (single actions or Event)
bull Process Eg Investigation (the entire lsquoexperimentalrsquo process)Eg Study (process of acquiring and treating the biological material)Eg Assay (process of performing some tests and recording the results)
31
32
33
Basic Formal Ontologya true upper level ontologyno interference with domain ontologiesno interference with physics cognitionno abstractano negative entitiesexplicit treatment of instances types and relations
34
Three dichotomies
instance vs type
continuant vs occurrent
dependent vs independent
everything in the ontology is a type
types exist in reality through their instances
35
instance vs type
experiments as instances
experiments as types
ontologies relate to types (kinds universals)
we need to keep track of instances in databases
36
BFO
ContinuantOccurrent(Process)
IndependentContinuant
DependentContinuant
37
BFO
ContinuantOccurrent(Process)
IndependentContinuant
(molecule cell organorganism)
DependentContinuant
(quality functiondisease)
Functioning Side-Effect Stochastic Process
38
BFO
ContinuantOccurrent(Process)
IndependentContinuant
(molecule cell organorganism)
PATO Functioning Side-Effect Stochastic Process
39
Unifying goal integration
Integrating datandash within and across these domainsndash across levels of granularityndash across different perspectives
Requiresndash Rigorous formal definitions in both ontologies
and annotation schemas
40
Some thoughts on the ontology itself
Outlinendash Definitions
bull how do we define PATO termsbull what exactly is it wersquore defining
ndash is_a hierarchybull what are the top-level distinctionsbull what are the finer grained distinctions
ndash shapes and colors
41
Itrsquos all about the definitions
OBO Foundry Principlendash Definitions should describe things in reality
not how terms are usedbull definitions should not use the word lsquodescribingrsquo
Scope of PATO = Phenotypic qualities
42
Old PATOEntity ndash Attribute ndash Value
Eye ndash Red ndash Dark
New PATOEntity ndash Quality
Eye ndash Red Eye ndash Dark Red
Dark Red is_a Red
43
What a quality is NOT
Qualities are not measurementsndash Instances of qualities exist independently of their
measurementsndash Qualities can have zero or more measurements
These are not the names of qualitiesndash percentagendash processndash abnormalndash high
44
Some examples of qualities
The particular redness of the left eye of a single individual flyndash An instance of a quality type
The color lsquoredrsquondash A quality type
Note the eye does not instantiate lsquoredrsquo
PATO represents quality types (universals)ndash PATO definitions can be used to classify quality
instances by the types they instantiate
45
the particular case ofredness (of a particularfly eye)
the type ldquoredrdquo
instantiates
an instance of an eye(in a particular fly)
the type ldquoeyerdquo
instantiates
inheresin (is aquality ofhas_bearer)
46
Qualities are dependent entities
Qualities require bearersndash Bearers can be physical objects or processes
Examplendash A shape requires a physical object to bear itndash If the physical object ceases to exist (eg it
decomposes) then the shape ceases to exist
48
Scale Bearer Quality Definition (proposed)
Physical Continuant Mass Equivalent to the sum of the mass of the parts of the bearer (mass at the particle level is primitiveoutwith PATO)
Physical Continuant Opacity An optical quality manifest by the capacity of the bearer to block light
PhysChem Liquid Concentration A compositional relational quality manifest by the relative quantity of some chemical type contained by the bearer
Molecular Gene splicing quality manifest by the splicing processes undergone by the bearer
Cellular Cell ploidy A cellular quality manifest by the number of genomes that are part of the bearer
Cellular Cell transformative potency
A cellular quality manifest by the capacity of the bearer cell to differentiate to different cell types
Organismal Tissue tone
Organismal Organism reproductive quality
49
How many types of shape are there
notched T-shaped Y-shaped branched unbranched antrose retrose curled curved wiggly squiggly round flat square oblong elliptical ovoid cuboid spherical egg-shaped rod-shaped heart-shaped hellip
How do we define them
How do we compare them
Shapes cannot be organized in a linear scale
Compare problem of classifying RNA structures
50
Standard case monadic qualitiesExamples
ndash E=kidney Q=hypertrophiedndash autodef a kidney which is hypertrophied
We assume that there is more contextual data (not shown)ndash eg genotype environment number of organisms
in study that showed phenotype
Interpretation (with the rest of the database record)ndash all fish in this experiment with a particular
genotype had a hypertrophied kidney at some point in time
51
Who should use PATO
Originallyndash model organism mutant phenotypes
But alsondash ontology-based evolutionary systematicsndash neuroscience BIRNndash clinical uses
bull OMIMbull clinical records (clinical manifestations)bull drug effects chemical effects
ndash to define terms in other ontologiesbull eg diploid cell invasive tumor engineered gene
condensed chromosome
- The Ontology of Experiments + PATO
- Plan
- EXPO
- Slide 4
- EXPO Formalisation of Science
- Slide 6
- Slide 7
- Slide 8
- Suggested Upper Merged Ontology
- SUMO top level
- Suggested Upper Merged Ontology
- SUMO Structure
- SUMO+Domain Ontology
- Slide 14
- Slide 15
- advantages of SUMO
- problems with SUMO as Upper-Level
- Slide 18
- Slide 19
- Slide 20
- Slide 21
- OBI
- Overview of the Ontology of Biomedical Investigations
- OBI neacutee FuGO
- Motivation for OBI
- Emerging FuGO Design Principles
- OBI Collaborating Communities
- Slide 28
- Slide 29
- FuGO - Top Level Universals
- Slide 31
- Slide 32
- Basic Formal Ontology
- Three dichotomies
- instance vs type
- BFO
- Slide 37
- Slide 38
- Unifying goal integration
- Some thoughts on the ontology itself
- Itrsquos all about the definitions
- Old PATO Entity ndash Attribute ndash Value Eye ndash Red ndash Dark
- What a quality is NOT
- Some examples of qualities
- Slide 45
- Qualities are dependent entities
- Slide 48
- How many types of shape are there
- Standard case monadic qualities
- Who should use PATO
-
9
Suggested Upper Merged Ontology
Adam Peaseapeasearticulatesoftwarecomhttpwwwarticulatesoftwarecom
10
SUMO top levelEntity
ndash Physical bull Object
ndash SelfConnectedObject raquo Substance raquo CorpuscularObject raquo Food
ndash Region ndash Collection ndash Agent
bull Process ndash Abstract
bull SetOrClass bull Relation bull Quantity
ndash Number ndash PhysicalQuantity
bull Attribute bull Proposition
11
Suggested Upper Merged Ontology
1000 terms 4000 axioms 750 rules
Associated domain ontologies totalling 20000 terms and 60000 axioms
[includes ontology of boundaries from BS]
12
SUMO Structure
Structural Ontology
Base Ontology
SetClass Theory Numeric Temporal Mereotopology
Graph Measure Processes Objects
Qualities
13
SUMO+Domain OntologyStructuralOntology
BaseOntology
SetClassTheory
Numeric Temporal Mereotopology
Graph Measure Processes Objects
Qualities
SUMO
Mid-Level
Military
Geography
Elements
Terrorist Attack Types
Communications
People
TransnationalIssues Financial
Ontology
TerroristEconomy
NAICSTerroristAttacks
hellip
FranceAfghanistan
UnitedStates
DistributedComputing
BiologicalViruses
WMD
ECommerceServices
Government
Transportation
WorldAirports
Total Terms Total Axioms Rules
20399 67108 2500
14
entity physical object process dual object process intentional process intentional psychological process recreation or exercise organizational process guiding keeping maintaining repairing poking content development making constructing manufacture publication cooking searching social interaction maneuver motion internal change shape change abstract
15
corpuscular object =defA SelfConnectedObject whose parts have properties that are not shared by the whole
Subclass(es)organic object artifact
Coordinate term(s)content bearing object food substance
Axiom corpuscular object is disjoint from substance
substance =defAn Object in which every part is similar to every other in every relevant respect
16
advantages of SUMO
clear logical infrastructure FOL (too expressive for decidability more intuitive (human friendly) than eg OWL)
much more coherent than eg CYC upper level
much more coherent than the upper level hard wired into OWL-DL (and a fortiori into OWL-FULL)
FOL
17
problems with SUMO as Upper-Levelit contains its own tiny biology (protein
crustacean fruit-Or-vegetable )
it is overwhelmingly an ontology for abstract entities (sets functions in the mathematical sense )
no clear treatment of relations between instances vs relations between types
[all of these problems can be fixed]
18EXPO Experiment Ontology
19
representational style part_of experimental hypothesisexperimental actions part_of experimental design
20equipment part_of experimental design(confuses object with specification)
21
22
OBI
The Ontology of Biomedical Investigations
grew out of FuGE FuGO MGED PSI development activities
23
Overview of the Ontology of Biomedical Investigations
with thanks to Trish Whetzel (FuGO Working Group)
24
OBI neacutee FuGOPurpose
Provide a resource for the unambiguous description of the components of biomedical investigations such as the design protocols and instrumentation material data and types of analysis and statistical tools applied to the data NOT designed to model biology
Enables consistent annotation of data across different
technological and biological domains powerful queries semantically-driven data integration
25
Motivation for OBI
Standardization efforts in biological and technological domains Standard syntax - Data exchange formats
To provide a mechanism for software interoperability eg FuGE Object Model
Standard semantics - Controlled vocabularies or ontology Centralize commonalities for annotation term
needs across domains to describe an investigationstudyexperiment eg FuGO
26
Emerging FuGO Design Principles
OBO Foundry ontology utilize ontology best practices Inherit top level classes from an Upper Level ontology Use of the Relation Ontology Follow additional OBO Foundry principles Facilitates interoperability with other OBO Foundry
ontologiesOpen source approach
ProteacutegeacuteOWL Weekly conference calls Shared environment using Sourceforge (SF) and SF
mailing lists
27
OBI Collaborating CommunitiesCrop sciences Generation Challenge Programme (GCP)Environmental genomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiGenomic Standards Consortium (GSC)
wwwgenomicscehacukgenomecatalogueHUPO Proteomics Standards Initiative (PSI) psidevsourceforgenetImmunology Database and Analysis Portal wwwimmportorgImmune Epitope Database and Analysis Resource (IEDB)
httpwwwimmuneepitopeorghomedoInternational Society for Analytical Cytology httpwwwisac-netorgMetabolomics Standards Initiative (MSI) Neurogenetics Biomedical Informatics Research Network (BIRN)Nutrigenomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiPolymorphismToxicogenomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiTranscriptomics MGED Ontology Group
28
29
30
FuGO - Top Level Universals Continuant an entity that endureremains the same through time
bull Dependent Continuant depend on another entityEg Environment (depend on the set of ranges of conditions eg geographic location)
Eg Characteristics (entity that can be measured eg temperature unit)
- Realizable an entity that is realizable through a process (executedrun)Eg Software (a set of machine instructions)
Eg Design (the plan that can be realized in a process)
Eg Role (the part played by an entity within the context of a process)
bull Independent Continuant stands on its ownEg All physical entity (instrument technology platform document etc)
Eg Biological material (organism population etc)
Occurrent an entity that occursunfold in timebull Eg Temporal Regions Spatio-Temporal Regions (single actions or Event)
bull Process Eg Investigation (the entire lsquoexperimentalrsquo process)Eg Study (process of acquiring and treating the biological material)Eg Assay (process of performing some tests and recording the results)
31
32
33
Basic Formal Ontologya true upper level ontologyno interference with domain ontologiesno interference with physics cognitionno abstractano negative entitiesexplicit treatment of instances types and relations
34
Three dichotomies
instance vs type
continuant vs occurrent
dependent vs independent
everything in the ontology is a type
types exist in reality through their instances
35
instance vs type
experiments as instances
experiments as types
ontologies relate to types (kinds universals)
we need to keep track of instances in databases
36
BFO
ContinuantOccurrent(Process)
IndependentContinuant
DependentContinuant
37
BFO
ContinuantOccurrent(Process)
IndependentContinuant
(molecule cell organorganism)
DependentContinuant
(quality functiondisease)
Functioning Side-Effect Stochastic Process
38
BFO
ContinuantOccurrent(Process)
IndependentContinuant
(molecule cell organorganism)
PATO Functioning Side-Effect Stochastic Process
39
Unifying goal integration
Integrating datandash within and across these domainsndash across levels of granularityndash across different perspectives
Requiresndash Rigorous formal definitions in both ontologies
and annotation schemas
40
Some thoughts on the ontology itself
Outlinendash Definitions
bull how do we define PATO termsbull what exactly is it wersquore defining
ndash is_a hierarchybull what are the top-level distinctionsbull what are the finer grained distinctions
ndash shapes and colors
41
Itrsquos all about the definitions
OBO Foundry Principlendash Definitions should describe things in reality
not how terms are usedbull definitions should not use the word lsquodescribingrsquo
Scope of PATO = Phenotypic qualities
42
Old PATOEntity ndash Attribute ndash Value
Eye ndash Red ndash Dark
New PATOEntity ndash Quality
Eye ndash Red Eye ndash Dark Red
Dark Red is_a Red
43
What a quality is NOT
Qualities are not measurementsndash Instances of qualities exist independently of their
measurementsndash Qualities can have zero or more measurements
These are not the names of qualitiesndash percentagendash processndash abnormalndash high
44
Some examples of qualities
The particular redness of the left eye of a single individual flyndash An instance of a quality type
The color lsquoredrsquondash A quality type
Note the eye does not instantiate lsquoredrsquo
PATO represents quality types (universals)ndash PATO definitions can be used to classify quality
instances by the types they instantiate
45
the particular case ofredness (of a particularfly eye)
the type ldquoredrdquo
instantiates
an instance of an eye(in a particular fly)
the type ldquoeyerdquo
instantiates
inheresin (is aquality ofhas_bearer)
46
Qualities are dependent entities
Qualities require bearersndash Bearers can be physical objects or processes
Examplendash A shape requires a physical object to bear itndash If the physical object ceases to exist (eg it
decomposes) then the shape ceases to exist
48
Scale Bearer Quality Definition (proposed)
Physical Continuant Mass Equivalent to the sum of the mass of the parts of the bearer (mass at the particle level is primitiveoutwith PATO)
Physical Continuant Opacity An optical quality manifest by the capacity of the bearer to block light
PhysChem Liquid Concentration A compositional relational quality manifest by the relative quantity of some chemical type contained by the bearer
Molecular Gene splicing quality manifest by the splicing processes undergone by the bearer
Cellular Cell ploidy A cellular quality manifest by the number of genomes that are part of the bearer
Cellular Cell transformative potency
A cellular quality manifest by the capacity of the bearer cell to differentiate to different cell types
Organismal Tissue tone
Organismal Organism reproductive quality
49
How many types of shape are there
notched T-shaped Y-shaped branched unbranched antrose retrose curled curved wiggly squiggly round flat square oblong elliptical ovoid cuboid spherical egg-shaped rod-shaped heart-shaped hellip
How do we define them
How do we compare them
Shapes cannot be organized in a linear scale
Compare problem of classifying RNA structures
50
Standard case monadic qualitiesExamples
ndash E=kidney Q=hypertrophiedndash autodef a kidney which is hypertrophied
We assume that there is more contextual data (not shown)ndash eg genotype environment number of organisms
in study that showed phenotype
Interpretation (with the rest of the database record)ndash all fish in this experiment with a particular
genotype had a hypertrophied kidney at some point in time
51
Who should use PATO
Originallyndash model organism mutant phenotypes
But alsondash ontology-based evolutionary systematicsndash neuroscience BIRNndash clinical uses
bull OMIMbull clinical records (clinical manifestations)bull drug effects chemical effects
ndash to define terms in other ontologiesbull eg diploid cell invasive tumor engineered gene
condensed chromosome
- The Ontology of Experiments + PATO
- Plan
- EXPO
- Slide 4
- EXPO Formalisation of Science
- Slide 6
- Slide 7
- Slide 8
- Suggested Upper Merged Ontology
- SUMO top level
- Suggested Upper Merged Ontology
- SUMO Structure
- SUMO+Domain Ontology
- Slide 14
- Slide 15
- advantages of SUMO
- problems with SUMO as Upper-Level
- Slide 18
- Slide 19
- Slide 20
- Slide 21
- OBI
- Overview of the Ontology of Biomedical Investigations
- OBI neacutee FuGO
- Motivation for OBI
- Emerging FuGO Design Principles
- OBI Collaborating Communities
- Slide 28
- Slide 29
- FuGO - Top Level Universals
- Slide 31
- Slide 32
- Basic Formal Ontology
- Three dichotomies
- instance vs type
- BFO
- Slide 37
- Slide 38
- Unifying goal integration
- Some thoughts on the ontology itself
- Itrsquos all about the definitions
- Old PATO Entity ndash Attribute ndash Value Eye ndash Red ndash Dark
- What a quality is NOT
- Some examples of qualities
- Slide 45
- Qualities are dependent entities
- Slide 48
- How many types of shape are there
- Standard case monadic qualities
- Who should use PATO
-
10
SUMO top levelEntity
ndash Physical bull Object
ndash SelfConnectedObject raquo Substance raquo CorpuscularObject raquo Food
ndash Region ndash Collection ndash Agent
bull Process ndash Abstract
bull SetOrClass bull Relation bull Quantity
ndash Number ndash PhysicalQuantity
bull Attribute bull Proposition
11
Suggested Upper Merged Ontology
1000 terms 4000 axioms 750 rules
Associated domain ontologies totalling 20000 terms and 60000 axioms
[includes ontology of boundaries from BS]
12
SUMO Structure
Structural Ontology
Base Ontology
SetClass Theory Numeric Temporal Mereotopology
Graph Measure Processes Objects
Qualities
13
SUMO+Domain OntologyStructuralOntology
BaseOntology
SetClassTheory
Numeric Temporal Mereotopology
Graph Measure Processes Objects
Qualities
SUMO
Mid-Level
Military
Geography
Elements
Terrorist Attack Types
Communications
People
TransnationalIssues Financial
Ontology
TerroristEconomy
NAICSTerroristAttacks
hellip
FranceAfghanistan
UnitedStates
DistributedComputing
BiologicalViruses
WMD
ECommerceServices
Government
Transportation
WorldAirports
Total Terms Total Axioms Rules
20399 67108 2500
14
entity physical object process dual object process intentional process intentional psychological process recreation or exercise organizational process guiding keeping maintaining repairing poking content development making constructing manufacture publication cooking searching social interaction maneuver motion internal change shape change abstract
15
corpuscular object =defA SelfConnectedObject whose parts have properties that are not shared by the whole
Subclass(es)organic object artifact
Coordinate term(s)content bearing object food substance
Axiom corpuscular object is disjoint from substance
substance =defAn Object in which every part is similar to every other in every relevant respect
16
advantages of SUMO
clear logical infrastructure FOL (too expressive for decidability more intuitive (human friendly) than eg OWL)
much more coherent than eg CYC upper level
much more coherent than the upper level hard wired into OWL-DL (and a fortiori into OWL-FULL)
FOL
17
problems with SUMO as Upper-Levelit contains its own tiny biology (protein
crustacean fruit-Or-vegetable )
it is overwhelmingly an ontology for abstract entities (sets functions in the mathematical sense )
no clear treatment of relations between instances vs relations between types
[all of these problems can be fixed]
18EXPO Experiment Ontology
19
representational style part_of experimental hypothesisexperimental actions part_of experimental design
20equipment part_of experimental design(confuses object with specification)
21
22
OBI
The Ontology of Biomedical Investigations
grew out of FuGE FuGO MGED PSI development activities
23
Overview of the Ontology of Biomedical Investigations
with thanks to Trish Whetzel (FuGO Working Group)
24
OBI neacutee FuGOPurpose
Provide a resource for the unambiguous description of the components of biomedical investigations such as the design protocols and instrumentation material data and types of analysis and statistical tools applied to the data NOT designed to model biology
Enables consistent annotation of data across different
technological and biological domains powerful queries semantically-driven data integration
25
Motivation for OBI
Standardization efforts in biological and technological domains Standard syntax - Data exchange formats
To provide a mechanism for software interoperability eg FuGE Object Model
Standard semantics - Controlled vocabularies or ontology Centralize commonalities for annotation term
needs across domains to describe an investigationstudyexperiment eg FuGO
26
Emerging FuGO Design Principles
OBO Foundry ontology utilize ontology best practices Inherit top level classes from an Upper Level ontology Use of the Relation Ontology Follow additional OBO Foundry principles Facilitates interoperability with other OBO Foundry
ontologiesOpen source approach
ProteacutegeacuteOWL Weekly conference calls Shared environment using Sourceforge (SF) and SF
mailing lists
27
OBI Collaborating CommunitiesCrop sciences Generation Challenge Programme (GCP)Environmental genomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiGenomic Standards Consortium (GSC)
wwwgenomicscehacukgenomecatalogueHUPO Proteomics Standards Initiative (PSI) psidevsourceforgenetImmunology Database and Analysis Portal wwwimmportorgImmune Epitope Database and Analysis Resource (IEDB)
httpwwwimmuneepitopeorghomedoInternational Society for Analytical Cytology httpwwwisac-netorgMetabolomics Standards Initiative (MSI) Neurogenetics Biomedical Informatics Research Network (BIRN)Nutrigenomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiPolymorphismToxicogenomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiTranscriptomics MGED Ontology Group
28
29
30
FuGO - Top Level Universals Continuant an entity that endureremains the same through time
bull Dependent Continuant depend on another entityEg Environment (depend on the set of ranges of conditions eg geographic location)
Eg Characteristics (entity that can be measured eg temperature unit)
- Realizable an entity that is realizable through a process (executedrun)Eg Software (a set of machine instructions)
Eg Design (the plan that can be realized in a process)
Eg Role (the part played by an entity within the context of a process)
bull Independent Continuant stands on its ownEg All physical entity (instrument technology platform document etc)
Eg Biological material (organism population etc)
Occurrent an entity that occursunfold in timebull Eg Temporal Regions Spatio-Temporal Regions (single actions or Event)
bull Process Eg Investigation (the entire lsquoexperimentalrsquo process)Eg Study (process of acquiring and treating the biological material)Eg Assay (process of performing some tests and recording the results)
31
32
33
Basic Formal Ontologya true upper level ontologyno interference with domain ontologiesno interference with physics cognitionno abstractano negative entitiesexplicit treatment of instances types and relations
34
Three dichotomies
instance vs type
continuant vs occurrent
dependent vs independent
everything in the ontology is a type
types exist in reality through their instances
35
instance vs type
experiments as instances
experiments as types
ontologies relate to types (kinds universals)
we need to keep track of instances in databases
36
BFO
ContinuantOccurrent(Process)
IndependentContinuant
DependentContinuant
37
BFO
ContinuantOccurrent(Process)
IndependentContinuant
(molecule cell organorganism)
DependentContinuant
(quality functiondisease)
Functioning Side-Effect Stochastic Process
38
BFO
ContinuantOccurrent(Process)
IndependentContinuant
(molecule cell organorganism)
PATO Functioning Side-Effect Stochastic Process
39
Unifying goal integration
Integrating datandash within and across these domainsndash across levels of granularityndash across different perspectives
Requiresndash Rigorous formal definitions in both ontologies
and annotation schemas
40
Some thoughts on the ontology itself
Outlinendash Definitions
bull how do we define PATO termsbull what exactly is it wersquore defining
ndash is_a hierarchybull what are the top-level distinctionsbull what are the finer grained distinctions
ndash shapes and colors
41
Itrsquos all about the definitions
OBO Foundry Principlendash Definitions should describe things in reality
not how terms are usedbull definitions should not use the word lsquodescribingrsquo
Scope of PATO = Phenotypic qualities
42
Old PATOEntity ndash Attribute ndash Value
Eye ndash Red ndash Dark
New PATOEntity ndash Quality
Eye ndash Red Eye ndash Dark Red
Dark Red is_a Red
43
What a quality is NOT
Qualities are not measurementsndash Instances of qualities exist independently of their
measurementsndash Qualities can have zero or more measurements
These are not the names of qualitiesndash percentagendash processndash abnormalndash high
44
Some examples of qualities
The particular redness of the left eye of a single individual flyndash An instance of a quality type
The color lsquoredrsquondash A quality type
Note the eye does not instantiate lsquoredrsquo
PATO represents quality types (universals)ndash PATO definitions can be used to classify quality
instances by the types they instantiate
45
the particular case ofredness (of a particularfly eye)
the type ldquoredrdquo
instantiates
an instance of an eye(in a particular fly)
the type ldquoeyerdquo
instantiates
inheresin (is aquality ofhas_bearer)
46
Qualities are dependent entities
Qualities require bearersndash Bearers can be physical objects or processes
Examplendash A shape requires a physical object to bear itndash If the physical object ceases to exist (eg it
decomposes) then the shape ceases to exist
48
Scale Bearer Quality Definition (proposed)
Physical Continuant Mass Equivalent to the sum of the mass of the parts of the bearer (mass at the particle level is primitiveoutwith PATO)
Physical Continuant Opacity An optical quality manifest by the capacity of the bearer to block light
PhysChem Liquid Concentration A compositional relational quality manifest by the relative quantity of some chemical type contained by the bearer
Molecular Gene splicing quality manifest by the splicing processes undergone by the bearer
Cellular Cell ploidy A cellular quality manifest by the number of genomes that are part of the bearer
Cellular Cell transformative potency
A cellular quality manifest by the capacity of the bearer cell to differentiate to different cell types
Organismal Tissue tone
Organismal Organism reproductive quality
49
How many types of shape are there
notched T-shaped Y-shaped branched unbranched antrose retrose curled curved wiggly squiggly round flat square oblong elliptical ovoid cuboid spherical egg-shaped rod-shaped heart-shaped hellip
How do we define them
How do we compare them
Shapes cannot be organized in a linear scale
Compare problem of classifying RNA structures
50
Standard case monadic qualitiesExamples
ndash E=kidney Q=hypertrophiedndash autodef a kidney which is hypertrophied
We assume that there is more contextual data (not shown)ndash eg genotype environment number of organisms
in study that showed phenotype
Interpretation (with the rest of the database record)ndash all fish in this experiment with a particular
genotype had a hypertrophied kidney at some point in time
51
Who should use PATO
Originallyndash model organism mutant phenotypes
But alsondash ontology-based evolutionary systematicsndash neuroscience BIRNndash clinical uses
bull OMIMbull clinical records (clinical manifestations)bull drug effects chemical effects
ndash to define terms in other ontologiesbull eg diploid cell invasive tumor engineered gene
condensed chromosome
- The Ontology of Experiments + PATO
- Plan
- EXPO
- Slide 4
- EXPO Formalisation of Science
- Slide 6
- Slide 7
- Slide 8
- Suggested Upper Merged Ontology
- SUMO top level
- Suggested Upper Merged Ontology
- SUMO Structure
- SUMO+Domain Ontology
- Slide 14
- Slide 15
- advantages of SUMO
- problems with SUMO as Upper-Level
- Slide 18
- Slide 19
- Slide 20
- Slide 21
- OBI
- Overview of the Ontology of Biomedical Investigations
- OBI neacutee FuGO
- Motivation for OBI
- Emerging FuGO Design Principles
- OBI Collaborating Communities
- Slide 28
- Slide 29
- FuGO - Top Level Universals
- Slide 31
- Slide 32
- Basic Formal Ontology
- Three dichotomies
- instance vs type
- BFO
- Slide 37
- Slide 38
- Unifying goal integration
- Some thoughts on the ontology itself
- Itrsquos all about the definitions
- Old PATO Entity ndash Attribute ndash Value Eye ndash Red ndash Dark
- What a quality is NOT
- Some examples of qualities
- Slide 45
- Qualities are dependent entities
- Slide 48
- How many types of shape are there
- Standard case monadic qualities
- Who should use PATO
-
11
Suggested Upper Merged Ontology
1000 terms 4000 axioms 750 rules
Associated domain ontologies totalling 20000 terms and 60000 axioms
[includes ontology of boundaries from BS]
12
SUMO Structure
Structural Ontology
Base Ontology
SetClass Theory Numeric Temporal Mereotopology
Graph Measure Processes Objects
Qualities
13
SUMO+Domain OntologyStructuralOntology
BaseOntology
SetClassTheory
Numeric Temporal Mereotopology
Graph Measure Processes Objects
Qualities
SUMO
Mid-Level
Military
Geography
Elements
Terrorist Attack Types
Communications
People
TransnationalIssues Financial
Ontology
TerroristEconomy
NAICSTerroristAttacks
hellip
FranceAfghanistan
UnitedStates
DistributedComputing
BiologicalViruses
WMD
ECommerceServices
Government
Transportation
WorldAirports
Total Terms Total Axioms Rules
20399 67108 2500
14
entity physical object process dual object process intentional process intentional psychological process recreation or exercise organizational process guiding keeping maintaining repairing poking content development making constructing manufacture publication cooking searching social interaction maneuver motion internal change shape change abstract
15
corpuscular object =defA SelfConnectedObject whose parts have properties that are not shared by the whole
Subclass(es)organic object artifact
Coordinate term(s)content bearing object food substance
Axiom corpuscular object is disjoint from substance
substance =defAn Object in which every part is similar to every other in every relevant respect
16
advantages of SUMO
clear logical infrastructure FOL (too expressive for decidability more intuitive (human friendly) than eg OWL)
much more coherent than eg CYC upper level
much more coherent than the upper level hard wired into OWL-DL (and a fortiori into OWL-FULL)
FOL
17
problems with SUMO as Upper-Levelit contains its own tiny biology (protein
crustacean fruit-Or-vegetable )
it is overwhelmingly an ontology for abstract entities (sets functions in the mathematical sense )
no clear treatment of relations between instances vs relations between types
[all of these problems can be fixed]
18EXPO Experiment Ontology
19
representational style part_of experimental hypothesisexperimental actions part_of experimental design
20equipment part_of experimental design(confuses object with specification)
21
22
OBI
The Ontology of Biomedical Investigations
grew out of FuGE FuGO MGED PSI development activities
23
Overview of the Ontology of Biomedical Investigations
with thanks to Trish Whetzel (FuGO Working Group)
24
OBI neacutee FuGOPurpose
Provide a resource for the unambiguous description of the components of biomedical investigations such as the design protocols and instrumentation material data and types of analysis and statistical tools applied to the data NOT designed to model biology
Enables consistent annotation of data across different
technological and biological domains powerful queries semantically-driven data integration
25
Motivation for OBI
Standardization efforts in biological and technological domains Standard syntax - Data exchange formats
To provide a mechanism for software interoperability eg FuGE Object Model
Standard semantics - Controlled vocabularies or ontology Centralize commonalities for annotation term
needs across domains to describe an investigationstudyexperiment eg FuGO
26
Emerging FuGO Design Principles
OBO Foundry ontology utilize ontology best practices Inherit top level classes from an Upper Level ontology Use of the Relation Ontology Follow additional OBO Foundry principles Facilitates interoperability with other OBO Foundry
ontologiesOpen source approach
ProteacutegeacuteOWL Weekly conference calls Shared environment using Sourceforge (SF) and SF
mailing lists
27
OBI Collaborating CommunitiesCrop sciences Generation Challenge Programme (GCP)Environmental genomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiGenomic Standards Consortium (GSC)
wwwgenomicscehacukgenomecatalogueHUPO Proteomics Standards Initiative (PSI) psidevsourceforgenetImmunology Database and Analysis Portal wwwimmportorgImmune Epitope Database and Analysis Resource (IEDB)
httpwwwimmuneepitopeorghomedoInternational Society for Analytical Cytology httpwwwisac-netorgMetabolomics Standards Initiative (MSI) Neurogenetics Biomedical Informatics Research Network (BIRN)Nutrigenomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiPolymorphismToxicogenomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiTranscriptomics MGED Ontology Group
28
29
30
FuGO - Top Level Universals Continuant an entity that endureremains the same through time
bull Dependent Continuant depend on another entityEg Environment (depend on the set of ranges of conditions eg geographic location)
Eg Characteristics (entity that can be measured eg temperature unit)
- Realizable an entity that is realizable through a process (executedrun)Eg Software (a set of machine instructions)
Eg Design (the plan that can be realized in a process)
Eg Role (the part played by an entity within the context of a process)
bull Independent Continuant stands on its ownEg All physical entity (instrument technology platform document etc)
Eg Biological material (organism population etc)
Occurrent an entity that occursunfold in timebull Eg Temporal Regions Spatio-Temporal Regions (single actions or Event)
bull Process Eg Investigation (the entire lsquoexperimentalrsquo process)Eg Study (process of acquiring and treating the biological material)Eg Assay (process of performing some tests and recording the results)
31
32
33
Basic Formal Ontologya true upper level ontologyno interference with domain ontologiesno interference with physics cognitionno abstractano negative entitiesexplicit treatment of instances types and relations
34
Three dichotomies
instance vs type
continuant vs occurrent
dependent vs independent
everything in the ontology is a type
types exist in reality through their instances
35
instance vs type
experiments as instances
experiments as types
ontologies relate to types (kinds universals)
we need to keep track of instances in databases
36
BFO
ContinuantOccurrent(Process)
IndependentContinuant
DependentContinuant
37
BFO
ContinuantOccurrent(Process)
IndependentContinuant
(molecule cell organorganism)
DependentContinuant
(quality functiondisease)
Functioning Side-Effect Stochastic Process
38
BFO
ContinuantOccurrent(Process)
IndependentContinuant
(molecule cell organorganism)
PATO Functioning Side-Effect Stochastic Process
39
Unifying goal integration
Integrating datandash within and across these domainsndash across levels of granularityndash across different perspectives
Requiresndash Rigorous formal definitions in both ontologies
and annotation schemas
40
Some thoughts on the ontology itself
Outlinendash Definitions
bull how do we define PATO termsbull what exactly is it wersquore defining
ndash is_a hierarchybull what are the top-level distinctionsbull what are the finer grained distinctions
ndash shapes and colors
41
Itrsquos all about the definitions
OBO Foundry Principlendash Definitions should describe things in reality
not how terms are usedbull definitions should not use the word lsquodescribingrsquo
Scope of PATO = Phenotypic qualities
42
Old PATOEntity ndash Attribute ndash Value
Eye ndash Red ndash Dark
New PATOEntity ndash Quality
Eye ndash Red Eye ndash Dark Red
Dark Red is_a Red
43
What a quality is NOT
Qualities are not measurementsndash Instances of qualities exist independently of their
measurementsndash Qualities can have zero or more measurements
These are not the names of qualitiesndash percentagendash processndash abnormalndash high
44
Some examples of qualities
The particular redness of the left eye of a single individual flyndash An instance of a quality type
The color lsquoredrsquondash A quality type
Note the eye does not instantiate lsquoredrsquo
PATO represents quality types (universals)ndash PATO definitions can be used to classify quality
instances by the types they instantiate
45
the particular case ofredness (of a particularfly eye)
the type ldquoredrdquo
instantiates
an instance of an eye(in a particular fly)
the type ldquoeyerdquo
instantiates
inheresin (is aquality ofhas_bearer)
46
Qualities are dependent entities
Qualities require bearersndash Bearers can be physical objects or processes
Examplendash A shape requires a physical object to bear itndash If the physical object ceases to exist (eg it
decomposes) then the shape ceases to exist
48
Scale Bearer Quality Definition (proposed)
Physical Continuant Mass Equivalent to the sum of the mass of the parts of the bearer (mass at the particle level is primitiveoutwith PATO)
Physical Continuant Opacity An optical quality manifest by the capacity of the bearer to block light
PhysChem Liquid Concentration A compositional relational quality manifest by the relative quantity of some chemical type contained by the bearer
Molecular Gene splicing quality manifest by the splicing processes undergone by the bearer
Cellular Cell ploidy A cellular quality manifest by the number of genomes that are part of the bearer
Cellular Cell transformative potency
A cellular quality manifest by the capacity of the bearer cell to differentiate to different cell types
Organismal Tissue tone
Organismal Organism reproductive quality
49
How many types of shape are there
notched T-shaped Y-shaped branched unbranched antrose retrose curled curved wiggly squiggly round flat square oblong elliptical ovoid cuboid spherical egg-shaped rod-shaped heart-shaped hellip
How do we define them
How do we compare them
Shapes cannot be organized in a linear scale
Compare problem of classifying RNA structures
50
Standard case monadic qualitiesExamples
ndash E=kidney Q=hypertrophiedndash autodef a kidney which is hypertrophied
We assume that there is more contextual data (not shown)ndash eg genotype environment number of organisms
in study that showed phenotype
Interpretation (with the rest of the database record)ndash all fish in this experiment with a particular
genotype had a hypertrophied kidney at some point in time
51
Who should use PATO
Originallyndash model organism mutant phenotypes
But alsondash ontology-based evolutionary systematicsndash neuroscience BIRNndash clinical uses
bull OMIMbull clinical records (clinical manifestations)bull drug effects chemical effects
ndash to define terms in other ontologiesbull eg diploid cell invasive tumor engineered gene
condensed chromosome
- The Ontology of Experiments + PATO
- Plan
- EXPO
- Slide 4
- EXPO Formalisation of Science
- Slide 6
- Slide 7
- Slide 8
- Suggested Upper Merged Ontology
- SUMO top level
- Suggested Upper Merged Ontology
- SUMO Structure
- SUMO+Domain Ontology
- Slide 14
- Slide 15
- advantages of SUMO
- problems with SUMO as Upper-Level
- Slide 18
- Slide 19
- Slide 20
- Slide 21
- OBI
- Overview of the Ontology of Biomedical Investigations
- OBI neacutee FuGO
- Motivation for OBI
- Emerging FuGO Design Principles
- OBI Collaborating Communities
- Slide 28
- Slide 29
- FuGO - Top Level Universals
- Slide 31
- Slide 32
- Basic Formal Ontology
- Three dichotomies
- instance vs type
- BFO
- Slide 37
- Slide 38
- Unifying goal integration
- Some thoughts on the ontology itself
- Itrsquos all about the definitions
- Old PATO Entity ndash Attribute ndash Value Eye ndash Red ndash Dark
- What a quality is NOT
- Some examples of qualities
- Slide 45
- Qualities are dependent entities
- Slide 48
- How many types of shape are there
- Standard case monadic qualities
- Who should use PATO
-
12
SUMO Structure
Structural Ontology
Base Ontology
SetClass Theory Numeric Temporal Mereotopology
Graph Measure Processes Objects
Qualities
13
SUMO+Domain OntologyStructuralOntology
BaseOntology
SetClassTheory
Numeric Temporal Mereotopology
Graph Measure Processes Objects
Qualities
SUMO
Mid-Level
Military
Geography
Elements
Terrorist Attack Types
Communications
People
TransnationalIssues Financial
Ontology
TerroristEconomy
NAICSTerroristAttacks
hellip
FranceAfghanistan
UnitedStates
DistributedComputing
BiologicalViruses
WMD
ECommerceServices
Government
Transportation
WorldAirports
Total Terms Total Axioms Rules
20399 67108 2500
14
entity physical object process dual object process intentional process intentional psychological process recreation or exercise organizational process guiding keeping maintaining repairing poking content development making constructing manufacture publication cooking searching social interaction maneuver motion internal change shape change abstract
15
corpuscular object =defA SelfConnectedObject whose parts have properties that are not shared by the whole
Subclass(es)organic object artifact
Coordinate term(s)content bearing object food substance
Axiom corpuscular object is disjoint from substance
substance =defAn Object in which every part is similar to every other in every relevant respect
16
advantages of SUMO
clear logical infrastructure FOL (too expressive for decidability more intuitive (human friendly) than eg OWL)
much more coherent than eg CYC upper level
much more coherent than the upper level hard wired into OWL-DL (and a fortiori into OWL-FULL)
FOL
17
problems with SUMO as Upper-Levelit contains its own tiny biology (protein
crustacean fruit-Or-vegetable )
it is overwhelmingly an ontology for abstract entities (sets functions in the mathematical sense )
no clear treatment of relations between instances vs relations between types
[all of these problems can be fixed]
18EXPO Experiment Ontology
19
representational style part_of experimental hypothesisexperimental actions part_of experimental design
20equipment part_of experimental design(confuses object with specification)
21
22
OBI
The Ontology of Biomedical Investigations
grew out of FuGE FuGO MGED PSI development activities
23
Overview of the Ontology of Biomedical Investigations
with thanks to Trish Whetzel (FuGO Working Group)
24
OBI neacutee FuGOPurpose
Provide a resource for the unambiguous description of the components of biomedical investigations such as the design protocols and instrumentation material data and types of analysis and statistical tools applied to the data NOT designed to model biology
Enables consistent annotation of data across different
technological and biological domains powerful queries semantically-driven data integration
25
Motivation for OBI
Standardization efforts in biological and technological domains Standard syntax - Data exchange formats
To provide a mechanism for software interoperability eg FuGE Object Model
Standard semantics - Controlled vocabularies or ontology Centralize commonalities for annotation term
needs across domains to describe an investigationstudyexperiment eg FuGO
26
Emerging FuGO Design Principles
OBO Foundry ontology utilize ontology best practices Inherit top level classes from an Upper Level ontology Use of the Relation Ontology Follow additional OBO Foundry principles Facilitates interoperability with other OBO Foundry
ontologiesOpen source approach
ProteacutegeacuteOWL Weekly conference calls Shared environment using Sourceforge (SF) and SF
mailing lists
27
OBI Collaborating CommunitiesCrop sciences Generation Challenge Programme (GCP)Environmental genomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiGenomic Standards Consortium (GSC)
wwwgenomicscehacukgenomecatalogueHUPO Proteomics Standards Initiative (PSI) psidevsourceforgenetImmunology Database and Analysis Portal wwwimmportorgImmune Epitope Database and Analysis Resource (IEDB)
httpwwwimmuneepitopeorghomedoInternational Society for Analytical Cytology httpwwwisac-netorgMetabolomics Standards Initiative (MSI) Neurogenetics Biomedical Informatics Research Network (BIRN)Nutrigenomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiPolymorphismToxicogenomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiTranscriptomics MGED Ontology Group
28
29
30
FuGO - Top Level Universals Continuant an entity that endureremains the same through time
bull Dependent Continuant depend on another entityEg Environment (depend on the set of ranges of conditions eg geographic location)
Eg Characteristics (entity that can be measured eg temperature unit)
- Realizable an entity that is realizable through a process (executedrun)Eg Software (a set of machine instructions)
Eg Design (the plan that can be realized in a process)
Eg Role (the part played by an entity within the context of a process)
bull Independent Continuant stands on its ownEg All physical entity (instrument technology platform document etc)
Eg Biological material (organism population etc)
Occurrent an entity that occursunfold in timebull Eg Temporal Regions Spatio-Temporal Regions (single actions or Event)
bull Process Eg Investigation (the entire lsquoexperimentalrsquo process)Eg Study (process of acquiring and treating the biological material)Eg Assay (process of performing some tests and recording the results)
31
32
33
Basic Formal Ontologya true upper level ontologyno interference with domain ontologiesno interference with physics cognitionno abstractano negative entitiesexplicit treatment of instances types and relations
34
Three dichotomies
instance vs type
continuant vs occurrent
dependent vs independent
everything in the ontology is a type
types exist in reality through their instances
35
instance vs type
experiments as instances
experiments as types
ontologies relate to types (kinds universals)
we need to keep track of instances in databases
36
BFO
ContinuantOccurrent(Process)
IndependentContinuant
DependentContinuant
37
BFO
ContinuantOccurrent(Process)
IndependentContinuant
(molecule cell organorganism)
DependentContinuant
(quality functiondisease)
Functioning Side-Effect Stochastic Process
38
BFO
ContinuantOccurrent(Process)
IndependentContinuant
(molecule cell organorganism)
PATO Functioning Side-Effect Stochastic Process
39
Unifying goal integration
Integrating datandash within and across these domainsndash across levels of granularityndash across different perspectives
Requiresndash Rigorous formal definitions in both ontologies
and annotation schemas
40
Some thoughts on the ontology itself
Outlinendash Definitions
bull how do we define PATO termsbull what exactly is it wersquore defining
ndash is_a hierarchybull what are the top-level distinctionsbull what are the finer grained distinctions
ndash shapes and colors
41
Itrsquos all about the definitions
OBO Foundry Principlendash Definitions should describe things in reality
not how terms are usedbull definitions should not use the word lsquodescribingrsquo
Scope of PATO = Phenotypic qualities
42
Old PATOEntity ndash Attribute ndash Value
Eye ndash Red ndash Dark
New PATOEntity ndash Quality
Eye ndash Red Eye ndash Dark Red
Dark Red is_a Red
43
What a quality is NOT
Qualities are not measurementsndash Instances of qualities exist independently of their
measurementsndash Qualities can have zero or more measurements
These are not the names of qualitiesndash percentagendash processndash abnormalndash high
44
Some examples of qualities
The particular redness of the left eye of a single individual flyndash An instance of a quality type
The color lsquoredrsquondash A quality type
Note the eye does not instantiate lsquoredrsquo
PATO represents quality types (universals)ndash PATO definitions can be used to classify quality
instances by the types they instantiate
45
the particular case ofredness (of a particularfly eye)
the type ldquoredrdquo
instantiates
an instance of an eye(in a particular fly)
the type ldquoeyerdquo
instantiates
inheresin (is aquality ofhas_bearer)
46
Qualities are dependent entities
Qualities require bearersndash Bearers can be physical objects or processes
Examplendash A shape requires a physical object to bear itndash If the physical object ceases to exist (eg it
decomposes) then the shape ceases to exist
48
Scale Bearer Quality Definition (proposed)
Physical Continuant Mass Equivalent to the sum of the mass of the parts of the bearer (mass at the particle level is primitiveoutwith PATO)
Physical Continuant Opacity An optical quality manifest by the capacity of the bearer to block light
PhysChem Liquid Concentration A compositional relational quality manifest by the relative quantity of some chemical type contained by the bearer
Molecular Gene splicing quality manifest by the splicing processes undergone by the bearer
Cellular Cell ploidy A cellular quality manifest by the number of genomes that are part of the bearer
Cellular Cell transformative potency
A cellular quality manifest by the capacity of the bearer cell to differentiate to different cell types
Organismal Tissue tone
Organismal Organism reproductive quality
49
How many types of shape are there
notched T-shaped Y-shaped branched unbranched antrose retrose curled curved wiggly squiggly round flat square oblong elliptical ovoid cuboid spherical egg-shaped rod-shaped heart-shaped hellip
How do we define them
How do we compare them
Shapes cannot be organized in a linear scale
Compare problem of classifying RNA structures
50
Standard case monadic qualitiesExamples
ndash E=kidney Q=hypertrophiedndash autodef a kidney which is hypertrophied
We assume that there is more contextual data (not shown)ndash eg genotype environment number of organisms
in study that showed phenotype
Interpretation (with the rest of the database record)ndash all fish in this experiment with a particular
genotype had a hypertrophied kidney at some point in time
51
Who should use PATO
Originallyndash model organism mutant phenotypes
But alsondash ontology-based evolutionary systematicsndash neuroscience BIRNndash clinical uses
bull OMIMbull clinical records (clinical manifestations)bull drug effects chemical effects
ndash to define terms in other ontologiesbull eg diploid cell invasive tumor engineered gene
condensed chromosome
- The Ontology of Experiments + PATO
- Plan
- EXPO
- Slide 4
- EXPO Formalisation of Science
- Slide 6
- Slide 7
- Slide 8
- Suggested Upper Merged Ontology
- SUMO top level
- Suggested Upper Merged Ontology
- SUMO Structure
- SUMO+Domain Ontology
- Slide 14
- Slide 15
- advantages of SUMO
- problems with SUMO as Upper-Level
- Slide 18
- Slide 19
- Slide 20
- Slide 21
- OBI
- Overview of the Ontology of Biomedical Investigations
- OBI neacutee FuGO
- Motivation for OBI
- Emerging FuGO Design Principles
- OBI Collaborating Communities
- Slide 28
- Slide 29
- FuGO - Top Level Universals
- Slide 31
- Slide 32
- Basic Formal Ontology
- Three dichotomies
- instance vs type
- BFO
- Slide 37
- Slide 38
- Unifying goal integration
- Some thoughts on the ontology itself
- Itrsquos all about the definitions
- Old PATO Entity ndash Attribute ndash Value Eye ndash Red ndash Dark
- What a quality is NOT
- Some examples of qualities
- Slide 45
- Qualities are dependent entities
- Slide 48
- How many types of shape are there
- Standard case monadic qualities
- Who should use PATO
-
13
SUMO+Domain OntologyStructuralOntology
BaseOntology
SetClassTheory
Numeric Temporal Mereotopology
Graph Measure Processes Objects
Qualities
SUMO
Mid-Level
Military
Geography
Elements
Terrorist Attack Types
Communications
People
TransnationalIssues Financial
Ontology
TerroristEconomy
NAICSTerroristAttacks
hellip
FranceAfghanistan
UnitedStates
DistributedComputing
BiologicalViruses
WMD
ECommerceServices
Government
Transportation
WorldAirports
Total Terms Total Axioms Rules
20399 67108 2500
14
entity physical object process dual object process intentional process intentional psychological process recreation or exercise organizational process guiding keeping maintaining repairing poking content development making constructing manufacture publication cooking searching social interaction maneuver motion internal change shape change abstract
15
corpuscular object =defA SelfConnectedObject whose parts have properties that are not shared by the whole
Subclass(es)organic object artifact
Coordinate term(s)content bearing object food substance
Axiom corpuscular object is disjoint from substance
substance =defAn Object in which every part is similar to every other in every relevant respect
16
advantages of SUMO
clear logical infrastructure FOL (too expressive for decidability more intuitive (human friendly) than eg OWL)
much more coherent than eg CYC upper level
much more coherent than the upper level hard wired into OWL-DL (and a fortiori into OWL-FULL)
FOL
17
problems with SUMO as Upper-Levelit contains its own tiny biology (protein
crustacean fruit-Or-vegetable )
it is overwhelmingly an ontology for abstract entities (sets functions in the mathematical sense )
no clear treatment of relations between instances vs relations between types
[all of these problems can be fixed]
18EXPO Experiment Ontology
19
representational style part_of experimental hypothesisexperimental actions part_of experimental design
20equipment part_of experimental design(confuses object with specification)
21
22
OBI
The Ontology of Biomedical Investigations
grew out of FuGE FuGO MGED PSI development activities
23
Overview of the Ontology of Biomedical Investigations
with thanks to Trish Whetzel (FuGO Working Group)
24
OBI neacutee FuGOPurpose
Provide a resource for the unambiguous description of the components of biomedical investigations such as the design protocols and instrumentation material data and types of analysis and statistical tools applied to the data NOT designed to model biology
Enables consistent annotation of data across different
technological and biological domains powerful queries semantically-driven data integration
25
Motivation for OBI
Standardization efforts in biological and technological domains Standard syntax - Data exchange formats
To provide a mechanism for software interoperability eg FuGE Object Model
Standard semantics - Controlled vocabularies or ontology Centralize commonalities for annotation term
needs across domains to describe an investigationstudyexperiment eg FuGO
26
Emerging FuGO Design Principles
OBO Foundry ontology utilize ontology best practices Inherit top level classes from an Upper Level ontology Use of the Relation Ontology Follow additional OBO Foundry principles Facilitates interoperability with other OBO Foundry
ontologiesOpen source approach
ProteacutegeacuteOWL Weekly conference calls Shared environment using Sourceforge (SF) and SF
mailing lists
27
OBI Collaborating CommunitiesCrop sciences Generation Challenge Programme (GCP)Environmental genomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiGenomic Standards Consortium (GSC)
wwwgenomicscehacukgenomecatalogueHUPO Proteomics Standards Initiative (PSI) psidevsourceforgenetImmunology Database and Analysis Portal wwwimmportorgImmune Epitope Database and Analysis Resource (IEDB)
httpwwwimmuneepitopeorghomedoInternational Society for Analytical Cytology httpwwwisac-netorgMetabolomics Standards Initiative (MSI) Neurogenetics Biomedical Informatics Research Network (BIRN)Nutrigenomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiPolymorphismToxicogenomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiTranscriptomics MGED Ontology Group
28
29
30
FuGO - Top Level Universals Continuant an entity that endureremains the same through time
bull Dependent Continuant depend on another entityEg Environment (depend on the set of ranges of conditions eg geographic location)
Eg Characteristics (entity that can be measured eg temperature unit)
- Realizable an entity that is realizable through a process (executedrun)Eg Software (a set of machine instructions)
Eg Design (the plan that can be realized in a process)
Eg Role (the part played by an entity within the context of a process)
bull Independent Continuant stands on its ownEg All physical entity (instrument technology platform document etc)
Eg Biological material (organism population etc)
Occurrent an entity that occursunfold in timebull Eg Temporal Regions Spatio-Temporal Regions (single actions or Event)
bull Process Eg Investigation (the entire lsquoexperimentalrsquo process)Eg Study (process of acquiring and treating the biological material)Eg Assay (process of performing some tests and recording the results)
31
32
33
Basic Formal Ontologya true upper level ontologyno interference with domain ontologiesno interference with physics cognitionno abstractano negative entitiesexplicit treatment of instances types and relations
34
Three dichotomies
instance vs type
continuant vs occurrent
dependent vs independent
everything in the ontology is a type
types exist in reality through their instances
35
instance vs type
experiments as instances
experiments as types
ontologies relate to types (kinds universals)
we need to keep track of instances in databases
36
BFO
ContinuantOccurrent(Process)
IndependentContinuant
DependentContinuant
37
BFO
ContinuantOccurrent(Process)
IndependentContinuant
(molecule cell organorganism)
DependentContinuant
(quality functiondisease)
Functioning Side-Effect Stochastic Process
38
BFO
ContinuantOccurrent(Process)
IndependentContinuant
(molecule cell organorganism)
PATO Functioning Side-Effect Stochastic Process
39
Unifying goal integration
Integrating datandash within and across these domainsndash across levels of granularityndash across different perspectives
Requiresndash Rigorous formal definitions in both ontologies
and annotation schemas
40
Some thoughts on the ontology itself
Outlinendash Definitions
bull how do we define PATO termsbull what exactly is it wersquore defining
ndash is_a hierarchybull what are the top-level distinctionsbull what are the finer grained distinctions
ndash shapes and colors
41
Itrsquos all about the definitions
OBO Foundry Principlendash Definitions should describe things in reality
not how terms are usedbull definitions should not use the word lsquodescribingrsquo
Scope of PATO = Phenotypic qualities
42
Old PATOEntity ndash Attribute ndash Value
Eye ndash Red ndash Dark
New PATOEntity ndash Quality
Eye ndash Red Eye ndash Dark Red
Dark Red is_a Red
43
What a quality is NOT
Qualities are not measurementsndash Instances of qualities exist independently of their
measurementsndash Qualities can have zero or more measurements
These are not the names of qualitiesndash percentagendash processndash abnormalndash high
44
Some examples of qualities
The particular redness of the left eye of a single individual flyndash An instance of a quality type
The color lsquoredrsquondash A quality type
Note the eye does not instantiate lsquoredrsquo
PATO represents quality types (universals)ndash PATO definitions can be used to classify quality
instances by the types they instantiate
45
the particular case ofredness (of a particularfly eye)
the type ldquoredrdquo
instantiates
an instance of an eye(in a particular fly)
the type ldquoeyerdquo
instantiates
inheresin (is aquality ofhas_bearer)
46
Qualities are dependent entities
Qualities require bearersndash Bearers can be physical objects or processes
Examplendash A shape requires a physical object to bear itndash If the physical object ceases to exist (eg it
decomposes) then the shape ceases to exist
48
Scale Bearer Quality Definition (proposed)
Physical Continuant Mass Equivalent to the sum of the mass of the parts of the bearer (mass at the particle level is primitiveoutwith PATO)
Physical Continuant Opacity An optical quality manifest by the capacity of the bearer to block light
PhysChem Liquid Concentration A compositional relational quality manifest by the relative quantity of some chemical type contained by the bearer
Molecular Gene splicing quality manifest by the splicing processes undergone by the bearer
Cellular Cell ploidy A cellular quality manifest by the number of genomes that are part of the bearer
Cellular Cell transformative potency
A cellular quality manifest by the capacity of the bearer cell to differentiate to different cell types
Organismal Tissue tone
Organismal Organism reproductive quality
49
How many types of shape are there
notched T-shaped Y-shaped branched unbranched antrose retrose curled curved wiggly squiggly round flat square oblong elliptical ovoid cuboid spherical egg-shaped rod-shaped heart-shaped hellip
How do we define them
How do we compare them
Shapes cannot be organized in a linear scale
Compare problem of classifying RNA structures
50
Standard case monadic qualitiesExamples
ndash E=kidney Q=hypertrophiedndash autodef a kidney which is hypertrophied
We assume that there is more contextual data (not shown)ndash eg genotype environment number of organisms
in study that showed phenotype
Interpretation (with the rest of the database record)ndash all fish in this experiment with a particular
genotype had a hypertrophied kidney at some point in time
51
Who should use PATO
Originallyndash model organism mutant phenotypes
But alsondash ontology-based evolutionary systematicsndash neuroscience BIRNndash clinical uses
bull OMIMbull clinical records (clinical manifestations)bull drug effects chemical effects
ndash to define terms in other ontologiesbull eg diploid cell invasive tumor engineered gene
condensed chromosome
- The Ontology of Experiments + PATO
- Plan
- EXPO
- Slide 4
- EXPO Formalisation of Science
- Slide 6
- Slide 7
- Slide 8
- Suggested Upper Merged Ontology
- SUMO top level
- Suggested Upper Merged Ontology
- SUMO Structure
- SUMO+Domain Ontology
- Slide 14
- Slide 15
- advantages of SUMO
- problems with SUMO as Upper-Level
- Slide 18
- Slide 19
- Slide 20
- Slide 21
- OBI
- Overview of the Ontology of Biomedical Investigations
- OBI neacutee FuGO
- Motivation for OBI
- Emerging FuGO Design Principles
- OBI Collaborating Communities
- Slide 28
- Slide 29
- FuGO - Top Level Universals
- Slide 31
- Slide 32
- Basic Formal Ontology
- Three dichotomies
- instance vs type
- BFO
- Slide 37
- Slide 38
- Unifying goal integration
- Some thoughts on the ontology itself
- Itrsquos all about the definitions
- Old PATO Entity ndash Attribute ndash Value Eye ndash Red ndash Dark
- What a quality is NOT
- Some examples of qualities
- Slide 45
- Qualities are dependent entities
- Slide 48
- How many types of shape are there
- Standard case monadic qualities
- Who should use PATO
-
14
entity physical object process dual object process intentional process intentional psychological process recreation or exercise organizational process guiding keeping maintaining repairing poking content development making constructing manufacture publication cooking searching social interaction maneuver motion internal change shape change abstract
15
corpuscular object =defA SelfConnectedObject whose parts have properties that are not shared by the whole
Subclass(es)organic object artifact
Coordinate term(s)content bearing object food substance
Axiom corpuscular object is disjoint from substance
substance =defAn Object in which every part is similar to every other in every relevant respect
16
advantages of SUMO
clear logical infrastructure FOL (too expressive for decidability more intuitive (human friendly) than eg OWL)
much more coherent than eg CYC upper level
much more coherent than the upper level hard wired into OWL-DL (and a fortiori into OWL-FULL)
FOL
17
problems with SUMO as Upper-Levelit contains its own tiny biology (protein
crustacean fruit-Or-vegetable )
it is overwhelmingly an ontology for abstract entities (sets functions in the mathematical sense )
no clear treatment of relations between instances vs relations between types
[all of these problems can be fixed]
18EXPO Experiment Ontology
19
representational style part_of experimental hypothesisexperimental actions part_of experimental design
20equipment part_of experimental design(confuses object with specification)
21
22
OBI
The Ontology of Biomedical Investigations
grew out of FuGE FuGO MGED PSI development activities
23
Overview of the Ontology of Biomedical Investigations
with thanks to Trish Whetzel (FuGO Working Group)
24
OBI neacutee FuGOPurpose
Provide a resource for the unambiguous description of the components of biomedical investigations such as the design protocols and instrumentation material data and types of analysis and statistical tools applied to the data NOT designed to model biology
Enables consistent annotation of data across different
technological and biological domains powerful queries semantically-driven data integration
25
Motivation for OBI
Standardization efforts in biological and technological domains Standard syntax - Data exchange formats
To provide a mechanism for software interoperability eg FuGE Object Model
Standard semantics - Controlled vocabularies or ontology Centralize commonalities for annotation term
needs across domains to describe an investigationstudyexperiment eg FuGO
26
Emerging FuGO Design Principles
OBO Foundry ontology utilize ontology best practices Inherit top level classes from an Upper Level ontology Use of the Relation Ontology Follow additional OBO Foundry principles Facilitates interoperability with other OBO Foundry
ontologiesOpen source approach
ProteacutegeacuteOWL Weekly conference calls Shared environment using Sourceforge (SF) and SF
mailing lists
27
OBI Collaborating CommunitiesCrop sciences Generation Challenge Programme (GCP)Environmental genomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiGenomic Standards Consortium (GSC)
wwwgenomicscehacukgenomecatalogueHUPO Proteomics Standards Initiative (PSI) psidevsourceforgenetImmunology Database and Analysis Portal wwwimmportorgImmune Epitope Database and Analysis Resource (IEDB)
httpwwwimmuneepitopeorghomedoInternational Society for Analytical Cytology httpwwwisac-netorgMetabolomics Standards Initiative (MSI) Neurogenetics Biomedical Informatics Research Network (BIRN)Nutrigenomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiPolymorphismToxicogenomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiTranscriptomics MGED Ontology Group
28
29
30
FuGO - Top Level Universals Continuant an entity that endureremains the same through time
bull Dependent Continuant depend on another entityEg Environment (depend on the set of ranges of conditions eg geographic location)
Eg Characteristics (entity that can be measured eg temperature unit)
- Realizable an entity that is realizable through a process (executedrun)Eg Software (a set of machine instructions)
Eg Design (the plan that can be realized in a process)
Eg Role (the part played by an entity within the context of a process)
bull Independent Continuant stands on its ownEg All physical entity (instrument technology platform document etc)
Eg Biological material (organism population etc)
Occurrent an entity that occursunfold in timebull Eg Temporal Regions Spatio-Temporal Regions (single actions or Event)
bull Process Eg Investigation (the entire lsquoexperimentalrsquo process)Eg Study (process of acquiring and treating the biological material)Eg Assay (process of performing some tests and recording the results)
31
32
33
Basic Formal Ontologya true upper level ontologyno interference with domain ontologiesno interference with physics cognitionno abstractano negative entitiesexplicit treatment of instances types and relations
34
Three dichotomies
instance vs type
continuant vs occurrent
dependent vs independent
everything in the ontology is a type
types exist in reality through their instances
35
instance vs type
experiments as instances
experiments as types
ontologies relate to types (kinds universals)
we need to keep track of instances in databases
36
BFO
ContinuantOccurrent(Process)
IndependentContinuant
DependentContinuant
37
BFO
ContinuantOccurrent(Process)
IndependentContinuant
(molecule cell organorganism)
DependentContinuant
(quality functiondisease)
Functioning Side-Effect Stochastic Process
38
BFO
ContinuantOccurrent(Process)
IndependentContinuant
(molecule cell organorganism)
PATO Functioning Side-Effect Stochastic Process
39
Unifying goal integration
Integrating datandash within and across these domainsndash across levels of granularityndash across different perspectives
Requiresndash Rigorous formal definitions in both ontologies
and annotation schemas
40
Some thoughts on the ontology itself
Outlinendash Definitions
bull how do we define PATO termsbull what exactly is it wersquore defining
ndash is_a hierarchybull what are the top-level distinctionsbull what are the finer grained distinctions
ndash shapes and colors
41
Itrsquos all about the definitions
OBO Foundry Principlendash Definitions should describe things in reality
not how terms are usedbull definitions should not use the word lsquodescribingrsquo
Scope of PATO = Phenotypic qualities
42
Old PATOEntity ndash Attribute ndash Value
Eye ndash Red ndash Dark
New PATOEntity ndash Quality
Eye ndash Red Eye ndash Dark Red
Dark Red is_a Red
43
What a quality is NOT
Qualities are not measurementsndash Instances of qualities exist independently of their
measurementsndash Qualities can have zero or more measurements
These are not the names of qualitiesndash percentagendash processndash abnormalndash high
44
Some examples of qualities
The particular redness of the left eye of a single individual flyndash An instance of a quality type
The color lsquoredrsquondash A quality type
Note the eye does not instantiate lsquoredrsquo
PATO represents quality types (universals)ndash PATO definitions can be used to classify quality
instances by the types they instantiate
45
the particular case ofredness (of a particularfly eye)
the type ldquoredrdquo
instantiates
an instance of an eye(in a particular fly)
the type ldquoeyerdquo
instantiates
inheresin (is aquality ofhas_bearer)
46
Qualities are dependent entities
Qualities require bearersndash Bearers can be physical objects or processes
Examplendash A shape requires a physical object to bear itndash If the physical object ceases to exist (eg it
decomposes) then the shape ceases to exist
48
Scale Bearer Quality Definition (proposed)
Physical Continuant Mass Equivalent to the sum of the mass of the parts of the bearer (mass at the particle level is primitiveoutwith PATO)
Physical Continuant Opacity An optical quality manifest by the capacity of the bearer to block light
PhysChem Liquid Concentration A compositional relational quality manifest by the relative quantity of some chemical type contained by the bearer
Molecular Gene splicing quality manifest by the splicing processes undergone by the bearer
Cellular Cell ploidy A cellular quality manifest by the number of genomes that are part of the bearer
Cellular Cell transformative potency
A cellular quality manifest by the capacity of the bearer cell to differentiate to different cell types
Organismal Tissue tone
Organismal Organism reproductive quality
49
How many types of shape are there
notched T-shaped Y-shaped branched unbranched antrose retrose curled curved wiggly squiggly round flat square oblong elliptical ovoid cuboid spherical egg-shaped rod-shaped heart-shaped hellip
How do we define them
How do we compare them
Shapes cannot be organized in a linear scale
Compare problem of classifying RNA structures
50
Standard case monadic qualitiesExamples
ndash E=kidney Q=hypertrophiedndash autodef a kidney which is hypertrophied
We assume that there is more contextual data (not shown)ndash eg genotype environment number of organisms
in study that showed phenotype
Interpretation (with the rest of the database record)ndash all fish in this experiment with a particular
genotype had a hypertrophied kidney at some point in time
51
Who should use PATO
Originallyndash model organism mutant phenotypes
But alsondash ontology-based evolutionary systematicsndash neuroscience BIRNndash clinical uses
bull OMIMbull clinical records (clinical manifestations)bull drug effects chemical effects
ndash to define terms in other ontologiesbull eg diploid cell invasive tumor engineered gene
condensed chromosome
- The Ontology of Experiments + PATO
- Plan
- EXPO
- Slide 4
- EXPO Formalisation of Science
- Slide 6
- Slide 7
- Slide 8
- Suggested Upper Merged Ontology
- SUMO top level
- Suggested Upper Merged Ontology
- SUMO Structure
- SUMO+Domain Ontology
- Slide 14
- Slide 15
- advantages of SUMO
- problems with SUMO as Upper-Level
- Slide 18
- Slide 19
- Slide 20
- Slide 21
- OBI
- Overview of the Ontology of Biomedical Investigations
- OBI neacutee FuGO
- Motivation for OBI
- Emerging FuGO Design Principles
- OBI Collaborating Communities
- Slide 28
- Slide 29
- FuGO - Top Level Universals
- Slide 31
- Slide 32
- Basic Formal Ontology
- Three dichotomies
- instance vs type
- BFO
- Slide 37
- Slide 38
- Unifying goal integration
- Some thoughts on the ontology itself
- Itrsquos all about the definitions
- Old PATO Entity ndash Attribute ndash Value Eye ndash Red ndash Dark
- What a quality is NOT
- Some examples of qualities
- Slide 45
- Qualities are dependent entities
- Slide 48
- How many types of shape are there
- Standard case monadic qualities
- Who should use PATO
-
15
corpuscular object =defA SelfConnectedObject whose parts have properties that are not shared by the whole
Subclass(es)organic object artifact
Coordinate term(s)content bearing object food substance
Axiom corpuscular object is disjoint from substance
substance =defAn Object in which every part is similar to every other in every relevant respect
16
advantages of SUMO
clear logical infrastructure FOL (too expressive for decidability more intuitive (human friendly) than eg OWL)
much more coherent than eg CYC upper level
much more coherent than the upper level hard wired into OWL-DL (and a fortiori into OWL-FULL)
FOL
17
problems with SUMO as Upper-Levelit contains its own tiny biology (protein
crustacean fruit-Or-vegetable )
it is overwhelmingly an ontology for abstract entities (sets functions in the mathematical sense )
no clear treatment of relations between instances vs relations between types
[all of these problems can be fixed]
18EXPO Experiment Ontology
19
representational style part_of experimental hypothesisexperimental actions part_of experimental design
20equipment part_of experimental design(confuses object with specification)
21
22
OBI
The Ontology of Biomedical Investigations
grew out of FuGE FuGO MGED PSI development activities
23
Overview of the Ontology of Biomedical Investigations
with thanks to Trish Whetzel (FuGO Working Group)
24
OBI neacutee FuGOPurpose
Provide a resource for the unambiguous description of the components of biomedical investigations such as the design protocols and instrumentation material data and types of analysis and statistical tools applied to the data NOT designed to model biology
Enables consistent annotation of data across different
technological and biological domains powerful queries semantically-driven data integration
25
Motivation for OBI
Standardization efforts in biological and technological domains Standard syntax - Data exchange formats
To provide a mechanism for software interoperability eg FuGE Object Model
Standard semantics - Controlled vocabularies or ontology Centralize commonalities for annotation term
needs across domains to describe an investigationstudyexperiment eg FuGO
26
Emerging FuGO Design Principles
OBO Foundry ontology utilize ontology best practices Inherit top level classes from an Upper Level ontology Use of the Relation Ontology Follow additional OBO Foundry principles Facilitates interoperability with other OBO Foundry
ontologiesOpen source approach
ProteacutegeacuteOWL Weekly conference calls Shared environment using Sourceforge (SF) and SF
mailing lists
27
OBI Collaborating CommunitiesCrop sciences Generation Challenge Programme (GCP)Environmental genomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiGenomic Standards Consortium (GSC)
wwwgenomicscehacukgenomecatalogueHUPO Proteomics Standards Initiative (PSI) psidevsourceforgenetImmunology Database and Analysis Portal wwwimmportorgImmune Epitope Database and Analysis Resource (IEDB)
httpwwwimmuneepitopeorghomedoInternational Society for Analytical Cytology httpwwwisac-netorgMetabolomics Standards Initiative (MSI) Neurogenetics Biomedical Informatics Research Network (BIRN)Nutrigenomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiPolymorphismToxicogenomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiTranscriptomics MGED Ontology Group
28
29
30
FuGO - Top Level Universals Continuant an entity that endureremains the same through time
bull Dependent Continuant depend on another entityEg Environment (depend on the set of ranges of conditions eg geographic location)
Eg Characteristics (entity that can be measured eg temperature unit)
- Realizable an entity that is realizable through a process (executedrun)Eg Software (a set of machine instructions)
Eg Design (the plan that can be realized in a process)
Eg Role (the part played by an entity within the context of a process)
bull Independent Continuant stands on its ownEg All physical entity (instrument technology platform document etc)
Eg Biological material (organism population etc)
Occurrent an entity that occursunfold in timebull Eg Temporal Regions Spatio-Temporal Regions (single actions or Event)
bull Process Eg Investigation (the entire lsquoexperimentalrsquo process)Eg Study (process of acquiring and treating the biological material)Eg Assay (process of performing some tests and recording the results)
31
32
33
Basic Formal Ontologya true upper level ontologyno interference with domain ontologiesno interference with physics cognitionno abstractano negative entitiesexplicit treatment of instances types and relations
34
Three dichotomies
instance vs type
continuant vs occurrent
dependent vs independent
everything in the ontology is a type
types exist in reality through their instances
35
instance vs type
experiments as instances
experiments as types
ontologies relate to types (kinds universals)
we need to keep track of instances in databases
36
BFO
ContinuantOccurrent(Process)
IndependentContinuant
DependentContinuant
37
BFO
ContinuantOccurrent(Process)
IndependentContinuant
(molecule cell organorganism)
DependentContinuant
(quality functiondisease)
Functioning Side-Effect Stochastic Process
38
BFO
ContinuantOccurrent(Process)
IndependentContinuant
(molecule cell organorganism)
PATO Functioning Side-Effect Stochastic Process
39
Unifying goal integration
Integrating datandash within and across these domainsndash across levels of granularityndash across different perspectives
Requiresndash Rigorous formal definitions in both ontologies
and annotation schemas
40
Some thoughts on the ontology itself
Outlinendash Definitions
bull how do we define PATO termsbull what exactly is it wersquore defining
ndash is_a hierarchybull what are the top-level distinctionsbull what are the finer grained distinctions
ndash shapes and colors
41
Itrsquos all about the definitions
OBO Foundry Principlendash Definitions should describe things in reality
not how terms are usedbull definitions should not use the word lsquodescribingrsquo
Scope of PATO = Phenotypic qualities
42
Old PATOEntity ndash Attribute ndash Value
Eye ndash Red ndash Dark
New PATOEntity ndash Quality
Eye ndash Red Eye ndash Dark Red
Dark Red is_a Red
43
What a quality is NOT
Qualities are not measurementsndash Instances of qualities exist independently of their
measurementsndash Qualities can have zero or more measurements
These are not the names of qualitiesndash percentagendash processndash abnormalndash high
44
Some examples of qualities
The particular redness of the left eye of a single individual flyndash An instance of a quality type
The color lsquoredrsquondash A quality type
Note the eye does not instantiate lsquoredrsquo
PATO represents quality types (universals)ndash PATO definitions can be used to classify quality
instances by the types they instantiate
45
the particular case ofredness (of a particularfly eye)
the type ldquoredrdquo
instantiates
an instance of an eye(in a particular fly)
the type ldquoeyerdquo
instantiates
inheresin (is aquality ofhas_bearer)
46
Qualities are dependent entities
Qualities require bearersndash Bearers can be physical objects or processes
Examplendash A shape requires a physical object to bear itndash If the physical object ceases to exist (eg it
decomposes) then the shape ceases to exist
48
Scale Bearer Quality Definition (proposed)
Physical Continuant Mass Equivalent to the sum of the mass of the parts of the bearer (mass at the particle level is primitiveoutwith PATO)
Physical Continuant Opacity An optical quality manifest by the capacity of the bearer to block light
PhysChem Liquid Concentration A compositional relational quality manifest by the relative quantity of some chemical type contained by the bearer
Molecular Gene splicing quality manifest by the splicing processes undergone by the bearer
Cellular Cell ploidy A cellular quality manifest by the number of genomes that are part of the bearer
Cellular Cell transformative potency
A cellular quality manifest by the capacity of the bearer cell to differentiate to different cell types
Organismal Tissue tone
Organismal Organism reproductive quality
49
How many types of shape are there
notched T-shaped Y-shaped branched unbranched antrose retrose curled curved wiggly squiggly round flat square oblong elliptical ovoid cuboid spherical egg-shaped rod-shaped heart-shaped hellip
How do we define them
How do we compare them
Shapes cannot be organized in a linear scale
Compare problem of classifying RNA structures
50
Standard case monadic qualitiesExamples
ndash E=kidney Q=hypertrophiedndash autodef a kidney which is hypertrophied
We assume that there is more contextual data (not shown)ndash eg genotype environment number of organisms
in study that showed phenotype
Interpretation (with the rest of the database record)ndash all fish in this experiment with a particular
genotype had a hypertrophied kidney at some point in time
51
Who should use PATO
Originallyndash model organism mutant phenotypes
But alsondash ontology-based evolutionary systematicsndash neuroscience BIRNndash clinical uses
bull OMIMbull clinical records (clinical manifestations)bull drug effects chemical effects
ndash to define terms in other ontologiesbull eg diploid cell invasive tumor engineered gene
condensed chromosome
- The Ontology of Experiments + PATO
- Plan
- EXPO
- Slide 4
- EXPO Formalisation of Science
- Slide 6
- Slide 7
- Slide 8
- Suggested Upper Merged Ontology
- SUMO top level
- Suggested Upper Merged Ontology
- SUMO Structure
- SUMO+Domain Ontology
- Slide 14
- Slide 15
- advantages of SUMO
- problems with SUMO as Upper-Level
- Slide 18
- Slide 19
- Slide 20
- Slide 21
- OBI
- Overview of the Ontology of Biomedical Investigations
- OBI neacutee FuGO
- Motivation for OBI
- Emerging FuGO Design Principles
- OBI Collaborating Communities
- Slide 28
- Slide 29
- FuGO - Top Level Universals
- Slide 31
- Slide 32
- Basic Formal Ontology
- Three dichotomies
- instance vs type
- BFO
- Slide 37
- Slide 38
- Unifying goal integration
- Some thoughts on the ontology itself
- Itrsquos all about the definitions
- Old PATO Entity ndash Attribute ndash Value Eye ndash Red ndash Dark
- What a quality is NOT
- Some examples of qualities
- Slide 45
- Qualities are dependent entities
- Slide 48
- How many types of shape are there
- Standard case monadic qualities
- Who should use PATO
-
16
advantages of SUMO
clear logical infrastructure FOL (too expressive for decidability more intuitive (human friendly) than eg OWL)
much more coherent than eg CYC upper level
much more coherent than the upper level hard wired into OWL-DL (and a fortiori into OWL-FULL)
FOL
17
problems with SUMO as Upper-Levelit contains its own tiny biology (protein
crustacean fruit-Or-vegetable )
it is overwhelmingly an ontology for abstract entities (sets functions in the mathematical sense )
no clear treatment of relations between instances vs relations between types
[all of these problems can be fixed]
18EXPO Experiment Ontology
19
representational style part_of experimental hypothesisexperimental actions part_of experimental design
20equipment part_of experimental design(confuses object with specification)
21
22
OBI
The Ontology of Biomedical Investigations
grew out of FuGE FuGO MGED PSI development activities
23
Overview of the Ontology of Biomedical Investigations
with thanks to Trish Whetzel (FuGO Working Group)
24
OBI neacutee FuGOPurpose
Provide a resource for the unambiguous description of the components of biomedical investigations such as the design protocols and instrumentation material data and types of analysis and statistical tools applied to the data NOT designed to model biology
Enables consistent annotation of data across different
technological and biological domains powerful queries semantically-driven data integration
25
Motivation for OBI
Standardization efforts in biological and technological domains Standard syntax - Data exchange formats
To provide a mechanism for software interoperability eg FuGE Object Model
Standard semantics - Controlled vocabularies or ontology Centralize commonalities for annotation term
needs across domains to describe an investigationstudyexperiment eg FuGO
26
Emerging FuGO Design Principles
OBO Foundry ontology utilize ontology best practices Inherit top level classes from an Upper Level ontology Use of the Relation Ontology Follow additional OBO Foundry principles Facilitates interoperability with other OBO Foundry
ontologiesOpen source approach
ProteacutegeacuteOWL Weekly conference calls Shared environment using Sourceforge (SF) and SF
mailing lists
27
OBI Collaborating CommunitiesCrop sciences Generation Challenge Programme (GCP)Environmental genomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiGenomic Standards Consortium (GSC)
wwwgenomicscehacukgenomecatalogueHUPO Proteomics Standards Initiative (PSI) psidevsourceforgenetImmunology Database and Analysis Portal wwwimmportorgImmune Epitope Database and Analysis Resource (IEDB)
httpwwwimmuneepitopeorghomedoInternational Society for Analytical Cytology httpwwwisac-netorgMetabolomics Standards Initiative (MSI) Neurogenetics Biomedical Informatics Research Network (BIRN)Nutrigenomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiPolymorphismToxicogenomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiTranscriptomics MGED Ontology Group
28
29
30
FuGO - Top Level Universals Continuant an entity that endureremains the same through time
bull Dependent Continuant depend on another entityEg Environment (depend on the set of ranges of conditions eg geographic location)
Eg Characteristics (entity that can be measured eg temperature unit)
- Realizable an entity that is realizable through a process (executedrun)Eg Software (a set of machine instructions)
Eg Design (the plan that can be realized in a process)
Eg Role (the part played by an entity within the context of a process)
bull Independent Continuant stands on its ownEg All physical entity (instrument technology platform document etc)
Eg Biological material (organism population etc)
Occurrent an entity that occursunfold in timebull Eg Temporal Regions Spatio-Temporal Regions (single actions or Event)
bull Process Eg Investigation (the entire lsquoexperimentalrsquo process)Eg Study (process of acquiring and treating the biological material)Eg Assay (process of performing some tests and recording the results)
31
32
33
Basic Formal Ontologya true upper level ontologyno interference with domain ontologiesno interference with physics cognitionno abstractano negative entitiesexplicit treatment of instances types and relations
34
Three dichotomies
instance vs type
continuant vs occurrent
dependent vs independent
everything in the ontology is a type
types exist in reality through their instances
35
instance vs type
experiments as instances
experiments as types
ontologies relate to types (kinds universals)
we need to keep track of instances in databases
36
BFO
ContinuantOccurrent(Process)
IndependentContinuant
DependentContinuant
37
BFO
ContinuantOccurrent(Process)
IndependentContinuant
(molecule cell organorganism)
DependentContinuant
(quality functiondisease)
Functioning Side-Effect Stochastic Process
38
BFO
ContinuantOccurrent(Process)
IndependentContinuant
(molecule cell organorganism)
PATO Functioning Side-Effect Stochastic Process
39
Unifying goal integration
Integrating datandash within and across these domainsndash across levels of granularityndash across different perspectives
Requiresndash Rigorous formal definitions in both ontologies
and annotation schemas
40
Some thoughts on the ontology itself
Outlinendash Definitions
bull how do we define PATO termsbull what exactly is it wersquore defining
ndash is_a hierarchybull what are the top-level distinctionsbull what are the finer grained distinctions
ndash shapes and colors
41
Itrsquos all about the definitions
OBO Foundry Principlendash Definitions should describe things in reality
not how terms are usedbull definitions should not use the word lsquodescribingrsquo
Scope of PATO = Phenotypic qualities
42
Old PATOEntity ndash Attribute ndash Value
Eye ndash Red ndash Dark
New PATOEntity ndash Quality
Eye ndash Red Eye ndash Dark Red
Dark Red is_a Red
43
What a quality is NOT
Qualities are not measurementsndash Instances of qualities exist independently of their
measurementsndash Qualities can have zero or more measurements
These are not the names of qualitiesndash percentagendash processndash abnormalndash high
44
Some examples of qualities
The particular redness of the left eye of a single individual flyndash An instance of a quality type
The color lsquoredrsquondash A quality type
Note the eye does not instantiate lsquoredrsquo
PATO represents quality types (universals)ndash PATO definitions can be used to classify quality
instances by the types they instantiate
45
the particular case ofredness (of a particularfly eye)
the type ldquoredrdquo
instantiates
an instance of an eye(in a particular fly)
the type ldquoeyerdquo
instantiates
inheresin (is aquality ofhas_bearer)
46
Qualities are dependent entities
Qualities require bearersndash Bearers can be physical objects or processes
Examplendash A shape requires a physical object to bear itndash If the physical object ceases to exist (eg it
decomposes) then the shape ceases to exist
48
Scale Bearer Quality Definition (proposed)
Physical Continuant Mass Equivalent to the sum of the mass of the parts of the bearer (mass at the particle level is primitiveoutwith PATO)
Physical Continuant Opacity An optical quality manifest by the capacity of the bearer to block light
PhysChem Liquid Concentration A compositional relational quality manifest by the relative quantity of some chemical type contained by the bearer
Molecular Gene splicing quality manifest by the splicing processes undergone by the bearer
Cellular Cell ploidy A cellular quality manifest by the number of genomes that are part of the bearer
Cellular Cell transformative potency
A cellular quality manifest by the capacity of the bearer cell to differentiate to different cell types
Organismal Tissue tone
Organismal Organism reproductive quality
49
How many types of shape are there
notched T-shaped Y-shaped branched unbranched antrose retrose curled curved wiggly squiggly round flat square oblong elliptical ovoid cuboid spherical egg-shaped rod-shaped heart-shaped hellip
How do we define them
How do we compare them
Shapes cannot be organized in a linear scale
Compare problem of classifying RNA structures
50
Standard case monadic qualitiesExamples
ndash E=kidney Q=hypertrophiedndash autodef a kidney which is hypertrophied
We assume that there is more contextual data (not shown)ndash eg genotype environment number of organisms
in study that showed phenotype
Interpretation (with the rest of the database record)ndash all fish in this experiment with a particular
genotype had a hypertrophied kidney at some point in time
51
Who should use PATO
Originallyndash model organism mutant phenotypes
But alsondash ontology-based evolutionary systematicsndash neuroscience BIRNndash clinical uses
bull OMIMbull clinical records (clinical manifestations)bull drug effects chemical effects
ndash to define terms in other ontologiesbull eg diploid cell invasive tumor engineered gene
condensed chromosome
- The Ontology of Experiments + PATO
- Plan
- EXPO
- Slide 4
- EXPO Formalisation of Science
- Slide 6
- Slide 7
- Slide 8
- Suggested Upper Merged Ontology
- SUMO top level
- Suggested Upper Merged Ontology
- SUMO Structure
- SUMO+Domain Ontology
- Slide 14
- Slide 15
- advantages of SUMO
- problems with SUMO as Upper-Level
- Slide 18
- Slide 19
- Slide 20
- Slide 21
- OBI
- Overview of the Ontology of Biomedical Investigations
- OBI neacutee FuGO
- Motivation for OBI
- Emerging FuGO Design Principles
- OBI Collaborating Communities
- Slide 28
- Slide 29
- FuGO - Top Level Universals
- Slide 31
- Slide 32
- Basic Formal Ontology
- Three dichotomies
- instance vs type
- BFO
- Slide 37
- Slide 38
- Unifying goal integration
- Some thoughts on the ontology itself
- Itrsquos all about the definitions
- Old PATO Entity ndash Attribute ndash Value Eye ndash Red ndash Dark
- What a quality is NOT
- Some examples of qualities
- Slide 45
- Qualities are dependent entities
- Slide 48
- How many types of shape are there
- Standard case monadic qualities
- Who should use PATO
-
17
problems with SUMO as Upper-Levelit contains its own tiny biology (protein
crustacean fruit-Or-vegetable )
it is overwhelmingly an ontology for abstract entities (sets functions in the mathematical sense )
no clear treatment of relations between instances vs relations between types
[all of these problems can be fixed]
18EXPO Experiment Ontology
19
representational style part_of experimental hypothesisexperimental actions part_of experimental design
20equipment part_of experimental design(confuses object with specification)
21
22
OBI
The Ontology of Biomedical Investigations
grew out of FuGE FuGO MGED PSI development activities
23
Overview of the Ontology of Biomedical Investigations
with thanks to Trish Whetzel (FuGO Working Group)
24
OBI neacutee FuGOPurpose
Provide a resource for the unambiguous description of the components of biomedical investigations such as the design protocols and instrumentation material data and types of analysis and statistical tools applied to the data NOT designed to model biology
Enables consistent annotation of data across different
technological and biological domains powerful queries semantically-driven data integration
25
Motivation for OBI
Standardization efforts in biological and technological domains Standard syntax - Data exchange formats
To provide a mechanism for software interoperability eg FuGE Object Model
Standard semantics - Controlled vocabularies or ontology Centralize commonalities for annotation term
needs across domains to describe an investigationstudyexperiment eg FuGO
26
Emerging FuGO Design Principles
OBO Foundry ontology utilize ontology best practices Inherit top level classes from an Upper Level ontology Use of the Relation Ontology Follow additional OBO Foundry principles Facilitates interoperability with other OBO Foundry
ontologiesOpen source approach
ProteacutegeacuteOWL Weekly conference calls Shared environment using Sourceforge (SF) and SF
mailing lists
27
OBI Collaborating CommunitiesCrop sciences Generation Challenge Programme (GCP)Environmental genomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiGenomic Standards Consortium (GSC)
wwwgenomicscehacukgenomecatalogueHUPO Proteomics Standards Initiative (PSI) psidevsourceforgenetImmunology Database and Analysis Portal wwwimmportorgImmune Epitope Database and Analysis Resource (IEDB)
httpwwwimmuneepitopeorghomedoInternational Society for Analytical Cytology httpwwwisac-netorgMetabolomics Standards Initiative (MSI) Neurogenetics Biomedical Informatics Research Network (BIRN)Nutrigenomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiPolymorphismToxicogenomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiTranscriptomics MGED Ontology Group
28
29
30
FuGO - Top Level Universals Continuant an entity that endureremains the same through time
bull Dependent Continuant depend on another entityEg Environment (depend on the set of ranges of conditions eg geographic location)
Eg Characteristics (entity that can be measured eg temperature unit)
- Realizable an entity that is realizable through a process (executedrun)Eg Software (a set of machine instructions)
Eg Design (the plan that can be realized in a process)
Eg Role (the part played by an entity within the context of a process)
bull Independent Continuant stands on its ownEg All physical entity (instrument technology platform document etc)
Eg Biological material (organism population etc)
Occurrent an entity that occursunfold in timebull Eg Temporal Regions Spatio-Temporal Regions (single actions or Event)
bull Process Eg Investigation (the entire lsquoexperimentalrsquo process)Eg Study (process of acquiring and treating the biological material)Eg Assay (process of performing some tests and recording the results)
31
32
33
Basic Formal Ontologya true upper level ontologyno interference with domain ontologiesno interference with physics cognitionno abstractano negative entitiesexplicit treatment of instances types and relations
34
Three dichotomies
instance vs type
continuant vs occurrent
dependent vs independent
everything in the ontology is a type
types exist in reality through their instances
35
instance vs type
experiments as instances
experiments as types
ontologies relate to types (kinds universals)
we need to keep track of instances in databases
36
BFO
ContinuantOccurrent(Process)
IndependentContinuant
DependentContinuant
37
BFO
ContinuantOccurrent(Process)
IndependentContinuant
(molecule cell organorganism)
DependentContinuant
(quality functiondisease)
Functioning Side-Effect Stochastic Process
38
BFO
ContinuantOccurrent(Process)
IndependentContinuant
(molecule cell organorganism)
PATO Functioning Side-Effect Stochastic Process
39
Unifying goal integration
Integrating datandash within and across these domainsndash across levels of granularityndash across different perspectives
Requiresndash Rigorous formal definitions in both ontologies
and annotation schemas
40
Some thoughts on the ontology itself
Outlinendash Definitions
bull how do we define PATO termsbull what exactly is it wersquore defining
ndash is_a hierarchybull what are the top-level distinctionsbull what are the finer grained distinctions
ndash shapes and colors
41
Itrsquos all about the definitions
OBO Foundry Principlendash Definitions should describe things in reality
not how terms are usedbull definitions should not use the word lsquodescribingrsquo
Scope of PATO = Phenotypic qualities
42
Old PATOEntity ndash Attribute ndash Value
Eye ndash Red ndash Dark
New PATOEntity ndash Quality
Eye ndash Red Eye ndash Dark Red
Dark Red is_a Red
43
What a quality is NOT
Qualities are not measurementsndash Instances of qualities exist independently of their
measurementsndash Qualities can have zero or more measurements
These are not the names of qualitiesndash percentagendash processndash abnormalndash high
44
Some examples of qualities
The particular redness of the left eye of a single individual flyndash An instance of a quality type
The color lsquoredrsquondash A quality type
Note the eye does not instantiate lsquoredrsquo
PATO represents quality types (universals)ndash PATO definitions can be used to classify quality
instances by the types they instantiate
45
the particular case ofredness (of a particularfly eye)
the type ldquoredrdquo
instantiates
an instance of an eye(in a particular fly)
the type ldquoeyerdquo
instantiates
inheresin (is aquality ofhas_bearer)
46
Qualities are dependent entities
Qualities require bearersndash Bearers can be physical objects or processes
Examplendash A shape requires a physical object to bear itndash If the physical object ceases to exist (eg it
decomposes) then the shape ceases to exist
48
Scale Bearer Quality Definition (proposed)
Physical Continuant Mass Equivalent to the sum of the mass of the parts of the bearer (mass at the particle level is primitiveoutwith PATO)
Physical Continuant Opacity An optical quality manifest by the capacity of the bearer to block light
PhysChem Liquid Concentration A compositional relational quality manifest by the relative quantity of some chemical type contained by the bearer
Molecular Gene splicing quality manifest by the splicing processes undergone by the bearer
Cellular Cell ploidy A cellular quality manifest by the number of genomes that are part of the bearer
Cellular Cell transformative potency
A cellular quality manifest by the capacity of the bearer cell to differentiate to different cell types
Organismal Tissue tone
Organismal Organism reproductive quality
49
How many types of shape are there
notched T-shaped Y-shaped branched unbranched antrose retrose curled curved wiggly squiggly round flat square oblong elliptical ovoid cuboid spherical egg-shaped rod-shaped heart-shaped hellip
How do we define them
How do we compare them
Shapes cannot be organized in a linear scale
Compare problem of classifying RNA structures
50
Standard case monadic qualitiesExamples
ndash E=kidney Q=hypertrophiedndash autodef a kidney which is hypertrophied
We assume that there is more contextual data (not shown)ndash eg genotype environment number of organisms
in study that showed phenotype
Interpretation (with the rest of the database record)ndash all fish in this experiment with a particular
genotype had a hypertrophied kidney at some point in time
51
Who should use PATO
Originallyndash model organism mutant phenotypes
But alsondash ontology-based evolutionary systematicsndash neuroscience BIRNndash clinical uses
bull OMIMbull clinical records (clinical manifestations)bull drug effects chemical effects
ndash to define terms in other ontologiesbull eg diploid cell invasive tumor engineered gene
condensed chromosome
- The Ontology of Experiments + PATO
- Plan
- EXPO
- Slide 4
- EXPO Formalisation of Science
- Slide 6
- Slide 7
- Slide 8
- Suggested Upper Merged Ontology
- SUMO top level
- Suggested Upper Merged Ontology
- SUMO Structure
- SUMO+Domain Ontology
- Slide 14
- Slide 15
- advantages of SUMO
- problems with SUMO as Upper-Level
- Slide 18
- Slide 19
- Slide 20
- Slide 21
- OBI
- Overview of the Ontology of Biomedical Investigations
- OBI neacutee FuGO
- Motivation for OBI
- Emerging FuGO Design Principles
- OBI Collaborating Communities
- Slide 28
- Slide 29
- FuGO - Top Level Universals
- Slide 31
- Slide 32
- Basic Formal Ontology
- Three dichotomies
- instance vs type
- BFO
- Slide 37
- Slide 38
- Unifying goal integration
- Some thoughts on the ontology itself
- Itrsquos all about the definitions
- Old PATO Entity ndash Attribute ndash Value Eye ndash Red ndash Dark
- What a quality is NOT
- Some examples of qualities
- Slide 45
- Qualities are dependent entities
- Slide 48
- How many types of shape are there
- Standard case monadic qualities
- Who should use PATO
-
18EXPO Experiment Ontology
19
representational style part_of experimental hypothesisexperimental actions part_of experimental design
20equipment part_of experimental design(confuses object with specification)
21
22
OBI
The Ontology of Biomedical Investigations
grew out of FuGE FuGO MGED PSI development activities
23
Overview of the Ontology of Biomedical Investigations
with thanks to Trish Whetzel (FuGO Working Group)
24
OBI neacutee FuGOPurpose
Provide a resource for the unambiguous description of the components of biomedical investigations such as the design protocols and instrumentation material data and types of analysis and statistical tools applied to the data NOT designed to model biology
Enables consistent annotation of data across different
technological and biological domains powerful queries semantically-driven data integration
25
Motivation for OBI
Standardization efforts in biological and technological domains Standard syntax - Data exchange formats
To provide a mechanism for software interoperability eg FuGE Object Model
Standard semantics - Controlled vocabularies or ontology Centralize commonalities for annotation term
needs across domains to describe an investigationstudyexperiment eg FuGO
26
Emerging FuGO Design Principles
OBO Foundry ontology utilize ontology best practices Inherit top level classes from an Upper Level ontology Use of the Relation Ontology Follow additional OBO Foundry principles Facilitates interoperability with other OBO Foundry
ontologiesOpen source approach
ProteacutegeacuteOWL Weekly conference calls Shared environment using Sourceforge (SF) and SF
mailing lists
27
OBI Collaborating CommunitiesCrop sciences Generation Challenge Programme (GCP)Environmental genomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiGenomic Standards Consortium (GSC)
wwwgenomicscehacukgenomecatalogueHUPO Proteomics Standards Initiative (PSI) psidevsourceforgenetImmunology Database and Analysis Portal wwwimmportorgImmune Epitope Database and Analysis Resource (IEDB)
httpwwwimmuneepitopeorghomedoInternational Society for Analytical Cytology httpwwwisac-netorgMetabolomics Standards Initiative (MSI) Neurogenetics Biomedical Informatics Research Network (BIRN)Nutrigenomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiPolymorphismToxicogenomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiTranscriptomics MGED Ontology Group
28
29
30
FuGO - Top Level Universals Continuant an entity that endureremains the same through time
bull Dependent Continuant depend on another entityEg Environment (depend on the set of ranges of conditions eg geographic location)
Eg Characteristics (entity that can be measured eg temperature unit)
- Realizable an entity that is realizable through a process (executedrun)Eg Software (a set of machine instructions)
Eg Design (the plan that can be realized in a process)
Eg Role (the part played by an entity within the context of a process)
bull Independent Continuant stands on its ownEg All physical entity (instrument technology platform document etc)
Eg Biological material (organism population etc)
Occurrent an entity that occursunfold in timebull Eg Temporal Regions Spatio-Temporal Regions (single actions or Event)
bull Process Eg Investigation (the entire lsquoexperimentalrsquo process)Eg Study (process of acquiring and treating the biological material)Eg Assay (process of performing some tests and recording the results)
31
32
33
Basic Formal Ontologya true upper level ontologyno interference with domain ontologiesno interference with physics cognitionno abstractano negative entitiesexplicit treatment of instances types and relations
34
Three dichotomies
instance vs type
continuant vs occurrent
dependent vs independent
everything in the ontology is a type
types exist in reality through their instances
35
instance vs type
experiments as instances
experiments as types
ontologies relate to types (kinds universals)
we need to keep track of instances in databases
36
BFO
ContinuantOccurrent(Process)
IndependentContinuant
DependentContinuant
37
BFO
ContinuantOccurrent(Process)
IndependentContinuant
(molecule cell organorganism)
DependentContinuant
(quality functiondisease)
Functioning Side-Effect Stochastic Process
38
BFO
ContinuantOccurrent(Process)
IndependentContinuant
(molecule cell organorganism)
PATO Functioning Side-Effect Stochastic Process
39
Unifying goal integration
Integrating datandash within and across these domainsndash across levels of granularityndash across different perspectives
Requiresndash Rigorous formal definitions in both ontologies
and annotation schemas
40
Some thoughts on the ontology itself
Outlinendash Definitions
bull how do we define PATO termsbull what exactly is it wersquore defining
ndash is_a hierarchybull what are the top-level distinctionsbull what are the finer grained distinctions
ndash shapes and colors
41
Itrsquos all about the definitions
OBO Foundry Principlendash Definitions should describe things in reality
not how terms are usedbull definitions should not use the word lsquodescribingrsquo
Scope of PATO = Phenotypic qualities
42
Old PATOEntity ndash Attribute ndash Value
Eye ndash Red ndash Dark
New PATOEntity ndash Quality
Eye ndash Red Eye ndash Dark Red
Dark Red is_a Red
43
What a quality is NOT
Qualities are not measurementsndash Instances of qualities exist independently of their
measurementsndash Qualities can have zero or more measurements
These are not the names of qualitiesndash percentagendash processndash abnormalndash high
44
Some examples of qualities
The particular redness of the left eye of a single individual flyndash An instance of a quality type
The color lsquoredrsquondash A quality type
Note the eye does not instantiate lsquoredrsquo
PATO represents quality types (universals)ndash PATO definitions can be used to classify quality
instances by the types they instantiate
45
the particular case ofredness (of a particularfly eye)
the type ldquoredrdquo
instantiates
an instance of an eye(in a particular fly)
the type ldquoeyerdquo
instantiates
inheresin (is aquality ofhas_bearer)
46
Qualities are dependent entities
Qualities require bearersndash Bearers can be physical objects or processes
Examplendash A shape requires a physical object to bear itndash If the physical object ceases to exist (eg it
decomposes) then the shape ceases to exist
48
Scale Bearer Quality Definition (proposed)
Physical Continuant Mass Equivalent to the sum of the mass of the parts of the bearer (mass at the particle level is primitiveoutwith PATO)
Physical Continuant Opacity An optical quality manifest by the capacity of the bearer to block light
PhysChem Liquid Concentration A compositional relational quality manifest by the relative quantity of some chemical type contained by the bearer
Molecular Gene splicing quality manifest by the splicing processes undergone by the bearer
Cellular Cell ploidy A cellular quality manifest by the number of genomes that are part of the bearer
Cellular Cell transformative potency
A cellular quality manifest by the capacity of the bearer cell to differentiate to different cell types
Organismal Tissue tone
Organismal Organism reproductive quality
49
How many types of shape are there
notched T-shaped Y-shaped branched unbranched antrose retrose curled curved wiggly squiggly round flat square oblong elliptical ovoid cuboid spherical egg-shaped rod-shaped heart-shaped hellip
How do we define them
How do we compare them
Shapes cannot be organized in a linear scale
Compare problem of classifying RNA structures
50
Standard case monadic qualitiesExamples
ndash E=kidney Q=hypertrophiedndash autodef a kidney which is hypertrophied
We assume that there is more contextual data (not shown)ndash eg genotype environment number of organisms
in study that showed phenotype
Interpretation (with the rest of the database record)ndash all fish in this experiment with a particular
genotype had a hypertrophied kidney at some point in time
51
Who should use PATO
Originallyndash model organism mutant phenotypes
But alsondash ontology-based evolutionary systematicsndash neuroscience BIRNndash clinical uses
bull OMIMbull clinical records (clinical manifestations)bull drug effects chemical effects
ndash to define terms in other ontologiesbull eg diploid cell invasive tumor engineered gene
condensed chromosome
- The Ontology of Experiments + PATO
- Plan
- EXPO
- Slide 4
- EXPO Formalisation of Science
- Slide 6
- Slide 7
- Slide 8
- Suggested Upper Merged Ontology
- SUMO top level
- Suggested Upper Merged Ontology
- SUMO Structure
- SUMO+Domain Ontology
- Slide 14
- Slide 15
- advantages of SUMO
- problems with SUMO as Upper-Level
- Slide 18
- Slide 19
- Slide 20
- Slide 21
- OBI
- Overview of the Ontology of Biomedical Investigations
- OBI neacutee FuGO
- Motivation for OBI
- Emerging FuGO Design Principles
- OBI Collaborating Communities
- Slide 28
- Slide 29
- FuGO - Top Level Universals
- Slide 31
- Slide 32
- Basic Formal Ontology
- Three dichotomies
- instance vs type
- BFO
- Slide 37
- Slide 38
- Unifying goal integration
- Some thoughts on the ontology itself
- Itrsquos all about the definitions
- Old PATO Entity ndash Attribute ndash Value Eye ndash Red ndash Dark
- What a quality is NOT
- Some examples of qualities
- Slide 45
- Qualities are dependent entities
- Slide 48
- How many types of shape are there
- Standard case monadic qualities
- Who should use PATO
-
19
representational style part_of experimental hypothesisexperimental actions part_of experimental design
20equipment part_of experimental design(confuses object with specification)
21
22
OBI
The Ontology of Biomedical Investigations
grew out of FuGE FuGO MGED PSI development activities
23
Overview of the Ontology of Biomedical Investigations
with thanks to Trish Whetzel (FuGO Working Group)
24
OBI neacutee FuGOPurpose
Provide a resource for the unambiguous description of the components of biomedical investigations such as the design protocols and instrumentation material data and types of analysis and statistical tools applied to the data NOT designed to model biology
Enables consistent annotation of data across different
technological and biological domains powerful queries semantically-driven data integration
25
Motivation for OBI
Standardization efforts in biological and technological domains Standard syntax - Data exchange formats
To provide a mechanism for software interoperability eg FuGE Object Model
Standard semantics - Controlled vocabularies or ontology Centralize commonalities for annotation term
needs across domains to describe an investigationstudyexperiment eg FuGO
26
Emerging FuGO Design Principles
OBO Foundry ontology utilize ontology best practices Inherit top level classes from an Upper Level ontology Use of the Relation Ontology Follow additional OBO Foundry principles Facilitates interoperability with other OBO Foundry
ontologiesOpen source approach
ProteacutegeacuteOWL Weekly conference calls Shared environment using Sourceforge (SF) and SF
mailing lists
27
OBI Collaborating CommunitiesCrop sciences Generation Challenge Programme (GCP)Environmental genomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiGenomic Standards Consortium (GSC)
wwwgenomicscehacukgenomecatalogueHUPO Proteomics Standards Initiative (PSI) psidevsourceforgenetImmunology Database and Analysis Portal wwwimmportorgImmune Epitope Database and Analysis Resource (IEDB)
httpwwwimmuneepitopeorghomedoInternational Society for Analytical Cytology httpwwwisac-netorgMetabolomics Standards Initiative (MSI) Neurogenetics Biomedical Informatics Research Network (BIRN)Nutrigenomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiPolymorphismToxicogenomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiTranscriptomics MGED Ontology Group
28
29
30
FuGO - Top Level Universals Continuant an entity that endureremains the same through time
bull Dependent Continuant depend on another entityEg Environment (depend on the set of ranges of conditions eg geographic location)
Eg Characteristics (entity that can be measured eg temperature unit)
- Realizable an entity that is realizable through a process (executedrun)Eg Software (a set of machine instructions)
Eg Design (the plan that can be realized in a process)
Eg Role (the part played by an entity within the context of a process)
bull Independent Continuant stands on its ownEg All physical entity (instrument technology platform document etc)
Eg Biological material (organism population etc)
Occurrent an entity that occursunfold in timebull Eg Temporal Regions Spatio-Temporal Regions (single actions or Event)
bull Process Eg Investigation (the entire lsquoexperimentalrsquo process)Eg Study (process of acquiring and treating the biological material)Eg Assay (process of performing some tests and recording the results)
31
32
33
Basic Formal Ontologya true upper level ontologyno interference with domain ontologiesno interference with physics cognitionno abstractano negative entitiesexplicit treatment of instances types and relations
34
Three dichotomies
instance vs type
continuant vs occurrent
dependent vs independent
everything in the ontology is a type
types exist in reality through their instances
35
instance vs type
experiments as instances
experiments as types
ontologies relate to types (kinds universals)
we need to keep track of instances in databases
36
BFO
ContinuantOccurrent(Process)
IndependentContinuant
DependentContinuant
37
BFO
ContinuantOccurrent(Process)
IndependentContinuant
(molecule cell organorganism)
DependentContinuant
(quality functiondisease)
Functioning Side-Effect Stochastic Process
38
BFO
ContinuantOccurrent(Process)
IndependentContinuant
(molecule cell organorganism)
PATO Functioning Side-Effect Stochastic Process
39
Unifying goal integration
Integrating datandash within and across these domainsndash across levels of granularityndash across different perspectives
Requiresndash Rigorous formal definitions in both ontologies
and annotation schemas
40
Some thoughts on the ontology itself
Outlinendash Definitions
bull how do we define PATO termsbull what exactly is it wersquore defining
ndash is_a hierarchybull what are the top-level distinctionsbull what are the finer grained distinctions
ndash shapes and colors
41
Itrsquos all about the definitions
OBO Foundry Principlendash Definitions should describe things in reality
not how terms are usedbull definitions should not use the word lsquodescribingrsquo
Scope of PATO = Phenotypic qualities
42
Old PATOEntity ndash Attribute ndash Value
Eye ndash Red ndash Dark
New PATOEntity ndash Quality
Eye ndash Red Eye ndash Dark Red
Dark Red is_a Red
43
What a quality is NOT
Qualities are not measurementsndash Instances of qualities exist independently of their
measurementsndash Qualities can have zero or more measurements
These are not the names of qualitiesndash percentagendash processndash abnormalndash high
44
Some examples of qualities
The particular redness of the left eye of a single individual flyndash An instance of a quality type
The color lsquoredrsquondash A quality type
Note the eye does not instantiate lsquoredrsquo
PATO represents quality types (universals)ndash PATO definitions can be used to classify quality
instances by the types they instantiate
45
the particular case ofredness (of a particularfly eye)
the type ldquoredrdquo
instantiates
an instance of an eye(in a particular fly)
the type ldquoeyerdquo
instantiates
inheresin (is aquality ofhas_bearer)
46
Qualities are dependent entities
Qualities require bearersndash Bearers can be physical objects or processes
Examplendash A shape requires a physical object to bear itndash If the physical object ceases to exist (eg it
decomposes) then the shape ceases to exist
48
Scale Bearer Quality Definition (proposed)
Physical Continuant Mass Equivalent to the sum of the mass of the parts of the bearer (mass at the particle level is primitiveoutwith PATO)
Physical Continuant Opacity An optical quality manifest by the capacity of the bearer to block light
PhysChem Liquid Concentration A compositional relational quality manifest by the relative quantity of some chemical type contained by the bearer
Molecular Gene splicing quality manifest by the splicing processes undergone by the bearer
Cellular Cell ploidy A cellular quality manifest by the number of genomes that are part of the bearer
Cellular Cell transformative potency
A cellular quality manifest by the capacity of the bearer cell to differentiate to different cell types
Organismal Tissue tone
Organismal Organism reproductive quality
49
How many types of shape are there
notched T-shaped Y-shaped branched unbranched antrose retrose curled curved wiggly squiggly round flat square oblong elliptical ovoid cuboid spherical egg-shaped rod-shaped heart-shaped hellip
How do we define them
How do we compare them
Shapes cannot be organized in a linear scale
Compare problem of classifying RNA structures
50
Standard case monadic qualitiesExamples
ndash E=kidney Q=hypertrophiedndash autodef a kidney which is hypertrophied
We assume that there is more contextual data (not shown)ndash eg genotype environment number of organisms
in study that showed phenotype
Interpretation (with the rest of the database record)ndash all fish in this experiment with a particular
genotype had a hypertrophied kidney at some point in time
51
Who should use PATO
Originallyndash model organism mutant phenotypes
But alsondash ontology-based evolutionary systematicsndash neuroscience BIRNndash clinical uses
bull OMIMbull clinical records (clinical manifestations)bull drug effects chemical effects
ndash to define terms in other ontologiesbull eg diploid cell invasive tumor engineered gene
condensed chromosome
- The Ontology of Experiments + PATO
- Plan
- EXPO
- Slide 4
- EXPO Formalisation of Science
- Slide 6
- Slide 7
- Slide 8
- Suggested Upper Merged Ontology
- SUMO top level
- Suggested Upper Merged Ontology
- SUMO Structure
- SUMO+Domain Ontology
- Slide 14
- Slide 15
- advantages of SUMO
- problems with SUMO as Upper-Level
- Slide 18
- Slide 19
- Slide 20
- Slide 21
- OBI
- Overview of the Ontology of Biomedical Investigations
- OBI neacutee FuGO
- Motivation for OBI
- Emerging FuGO Design Principles
- OBI Collaborating Communities
- Slide 28
- Slide 29
- FuGO - Top Level Universals
- Slide 31
- Slide 32
- Basic Formal Ontology
- Three dichotomies
- instance vs type
- BFO
- Slide 37
- Slide 38
- Unifying goal integration
- Some thoughts on the ontology itself
- Itrsquos all about the definitions
- Old PATO Entity ndash Attribute ndash Value Eye ndash Red ndash Dark
- What a quality is NOT
- Some examples of qualities
- Slide 45
- Qualities are dependent entities
- Slide 48
- How many types of shape are there
- Standard case monadic qualities
- Who should use PATO
-
20equipment part_of experimental design(confuses object with specification)
21
22
OBI
The Ontology of Biomedical Investigations
grew out of FuGE FuGO MGED PSI development activities
23
Overview of the Ontology of Biomedical Investigations
with thanks to Trish Whetzel (FuGO Working Group)
24
OBI neacutee FuGOPurpose
Provide a resource for the unambiguous description of the components of biomedical investigations such as the design protocols and instrumentation material data and types of analysis and statistical tools applied to the data NOT designed to model biology
Enables consistent annotation of data across different
technological and biological domains powerful queries semantically-driven data integration
25
Motivation for OBI
Standardization efforts in biological and technological domains Standard syntax - Data exchange formats
To provide a mechanism for software interoperability eg FuGE Object Model
Standard semantics - Controlled vocabularies or ontology Centralize commonalities for annotation term
needs across domains to describe an investigationstudyexperiment eg FuGO
26
Emerging FuGO Design Principles
OBO Foundry ontology utilize ontology best practices Inherit top level classes from an Upper Level ontology Use of the Relation Ontology Follow additional OBO Foundry principles Facilitates interoperability with other OBO Foundry
ontologiesOpen source approach
ProteacutegeacuteOWL Weekly conference calls Shared environment using Sourceforge (SF) and SF
mailing lists
27
OBI Collaborating CommunitiesCrop sciences Generation Challenge Programme (GCP)Environmental genomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiGenomic Standards Consortium (GSC)
wwwgenomicscehacukgenomecatalogueHUPO Proteomics Standards Initiative (PSI) psidevsourceforgenetImmunology Database and Analysis Portal wwwimmportorgImmune Epitope Database and Analysis Resource (IEDB)
httpwwwimmuneepitopeorghomedoInternational Society for Analytical Cytology httpwwwisac-netorgMetabolomics Standards Initiative (MSI) Neurogenetics Biomedical Informatics Research Network (BIRN)Nutrigenomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiPolymorphismToxicogenomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiTranscriptomics MGED Ontology Group
28
29
30
FuGO - Top Level Universals Continuant an entity that endureremains the same through time
bull Dependent Continuant depend on another entityEg Environment (depend on the set of ranges of conditions eg geographic location)
Eg Characteristics (entity that can be measured eg temperature unit)
- Realizable an entity that is realizable through a process (executedrun)Eg Software (a set of machine instructions)
Eg Design (the plan that can be realized in a process)
Eg Role (the part played by an entity within the context of a process)
bull Independent Continuant stands on its ownEg All physical entity (instrument technology platform document etc)
Eg Biological material (organism population etc)
Occurrent an entity that occursunfold in timebull Eg Temporal Regions Spatio-Temporal Regions (single actions or Event)
bull Process Eg Investigation (the entire lsquoexperimentalrsquo process)Eg Study (process of acquiring and treating the biological material)Eg Assay (process of performing some tests and recording the results)
31
32
33
Basic Formal Ontologya true upper level ontologyno interference with domain ontologiesno interference with physics cognitionno abstractano negative entitiesexplicit treatment of instances types and relations
34
Three dichotomies
instance vs type
continuant vs occurrent
dependent vs independent
everything in the ontology is a type
types exist in reality through their instances
35
instance vs type
experiments as instances
experiments as types
ontologies relate to types (kinds universals)
we need to keep track of instances in databases
36
BFO
ContinuantOccurrent(Process)
IndependentContinuant
DependentContinuant
37
BFO
ContinuantOccurrent(Process)
IndependentContinuant
(molecule cell organorganism)
DependentContinuant
(quality functiondisease)
Functioning Side-Effect Stochastic Process
38
BFO
ContinuantOccurrent(Process)
IndependentContinuant
(molecule cell organorganism)
PATO Functioning Side-Effect Stochastic Process
39
Unifying goal integration
Integrating datandash within and across these domainsndash across levels of granularityndash across different perspectives
Requiresndash Rigorous formal definitions in both ontologies
and annotation schemas
40
Some thoughts on the ontology itself
Outlinendash Definitions
bull how do we define PATO termsbull what exactly is it wersquore defining
ndash is_a hierarchybull what are the top-level distinctionsbull what are the finer grained distinctions
ndash shapes and colors
41
Itrsquos all about the definitions
OBO Foundry Principlendash Definitions should describe things in reality
not how terms are usedbull definitions should not use the word lsquodescribingrsquo
Scope of PATO = Phenotypic qualities
42
Old PATOEntity ndash Attribute ndash Value
Eye ndash Red ndash Dark
New PATOEntity ndash Quality
Eye ndash Red Eye ndash Dark Red
Dark Red is_a Red
43
What a quality is NOT
Qualities are not measurementsndash Instances of qualities exist independently of their
measurementsndash Qualities can have zero or more measurements
These are not the names of qualitiesndash percentagendash processndash abnormalndash high
44
Some examples of qualities
The particular redness of the left eye of a single individual flyndash An instance of a quality type
The color lsquoredrsquondash A quality type
Note the eye does not instantiate lsquoredrsquo
PATO represents quality types (universals)ndash PATO definitions can be used to classify quality
instances by the types they instantiate
45
the particular case ofredness (of a particularfly eye)
the type ldquoredrdquo
instantiates
an instance of an eye(in a particular fly)
the type ldquoeyerdquo
instantiates
inheresin (is aquality ofhas_bearer)
46
Qualities are dependent entities
Qualities require bearersndash Bearers can be physical objects or processes
Examplendash A shape requires a physical object to bear itndash If the physical object ceases to exist (eg it
decomposes) then the shape ceases to exist
48
Scale Bearer Quality Definition (proposed)
Physical Continuant Mass Equivalent to the sum of the mass of the parts of the bearer (mass at the particle level is primitiveoutwith PATO)
Physical Continuant Opacity An optical quality manifest by the capacity of the bearer to block light
PhysChem Liquid Concentration A compositional relational quality manifest by the relative quantity of some chemical type contained by the bearer
Molecular Gene splicing quality manifest by the splicing processes undergone by the bearer
Cellular Cell ploidy A cellular quality manifest by the number of genomes that are part of the bearer
Cellular Cell transformative potency
A cellular quality manifest by the capacity of the bearer cell to differentiate to different cell types
Organismal Tissue tone
Organismal Organism reproductive quality
49
How many types of shape are there
notched T-shaped Y-shaped branched unbranched antrose retrose curled curved wiggly squiggly round flat square oblong elliptical ovoid cuboid spherical egg-shaped rod-shaped heart-shaped hellip
How do we define them
How do we compare them
Shapes cannot be organized in a linear scale
Compare problem of classifying RNA structures
50
Standard case monadic qualitiesExamples
ndash E=kidney Q=hypertrophiedndash autodef a kidney which is hypertrophied
We assume that there is more contextual data (not shown)ndash eg genotype environment number of organisms
in study that showed phenotype
Interpretation (with the rest of the database record)ndash all fish in this experiment with a particular
genotype had a hypertrophied kidney at some point in time
51
Who should use PATO
Originallyndash model organism mutant phenotypes
But alsondash ontology-based evolutionary systematicsndash neuroscience BIRNndash clinical uses
bull OMIMbull clinical records (clinical manifestations)bull drug effects chemical effects
ndash to define terms in other ontologiesbull eg diploid cell invasive tumor engineered gene
condensed chromosome
- The Ontology of Experiments + PATO
- Plan
- EXPO
- Slide 4
- EXPO Formalisation of Science
- Slide 6
- Slide 7
- Slide 8
- Suggested Upper Merged Ontology
- SUMO top level
- Suggested Upper Merged Ontology
- SUMO Structure
- SUMO+Domain Ontology
- Slide 14
- Slide 15
- advantages of SUMO
- problems with SUMO as Upper-Level
- Slide 18
- Slide 19
- Slide 20
- Slide 21
- OBI
- Overview of the Ontology of Biomedical Investigations
- OBI neacutee FuGO
- Motivation for OBI
- Emerging FuGO Design Principles
- OBI Collaborating Communities
- Slide 28
- Slide 29
- FuGO - Top Level Universals
- Slide 31
- Slide 32
- Basic Formal Ontology
- Three dichotomies
- instance vs type
- BFO
- Slide 37
- Slide 38
- Unifying goal integration
- Some thoughts on the ontology itself
- Itrsquos all about the definitions
- Old PATO Entity ndash Attribute ndash Value Eye ndash Red ndash Dark
- What a quality is NOT
- Some examples of qualities
- Slide 45
- Qualities are dependent entities
- Slide 48
- How many types of shape are there
- Standard case monadic qualities
- Who should use PATO
-
21
22
OBI
The Ontology of Biomedical Investigations
grew out of FuGE FuGO MGED PSI development activities
23
Overview of the Ontology of Biomedical Investigations
with thanks to Trish Whetzel (FuGO Working Group)
24
OBI neacutee FuGOPurpose
Provide a resource for the unambiguous description of the components of biomedical investigations such as the design protocols and instrumentation material data and types of analysis and statistical tools applied to the data NOT designed to model biology
Enables consistent annotation of data across different
technological and biological domains powerful queries semantically-driven data integration
25
Motivation for OBI
Standardization efforts in biological and technological domains Standard syntax - Data exchange formats
To provide a mechanism for software interoperability eg FuGE Object Model
Standard semantics - Controlled vocabularies or ontology Centralize commonalities for annotation term
needs across domains to describe an investigationstudyexperiment eg FuGO
26
Emerging FuGO Design Principles
OBO Foundry ontology utilize ontology best practices Inherit top level classes from an Upper Level ontology Use of the Relation Ontology Follow additional OBO Foundry principles Facilitates interoperability with other OBO Foundry
ontologiesOpen source approach
ProteacutegeacuteOWL Weekly conference calls Shared environment using Sourceforge (SF) and SF
mailing lists
27
OBI Collaborating CommunitiesCrop sciences Generation Challenge Programme (GCP)Environmental genomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiGenomic Standards Consortium (GSC)
wwwgenomicscehacukgenomecatalogueHUPO Proteomics Standards Initiative (PSI) psidevsourceforgenetImmunology Database and Analysis Portal wwwimmportorgImmune Epitope Database and Analysis Resource (IEDB)
httpwwwimmuneepitopeorghomedoInternational Society for Analytical Cytology httpwwwisac-netorgMetabolomics Standards Initiative (MSI) Neurogenetics Biomedical Informatics Research Network (BIRN)Nutrigenomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiPolymorphismToxicogenomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiTranscriptomics MGED Ontology Group
28
29
30
FuGO - Top Level Universals Continuant an entity that endureremains the same through time
bull Dependent Continuant depend on another entityEg Environment (depend on the set of ranges of conditions eg geographic location)
Eg Characteristics (entity that can be measured eg temperature unit)
- Realizable an entity that is realizable through a process (executedrun)Eg Software (a set of machine instructions)
Eg Design (the plan that can be realized in a process)
Eg Role (the part played by an entity within the context of a process)
bull Independent Continuant stands on its ownEg All physical entity (instrument technology platform document etc)
Eg Biological material (organism population etc)
Occurrent an entity that occursunfold in timebull Eg Temporal Regions Spatio-Temporal Regions (single actions or Event)
bull Process Eg Investigation (the entire lsquoexperimentalrsquo process)Eg Study (process of acquiring and treating the biological material)Eg Assay (process of performing some tests and recording the results)
31
32
33
Basic Formal Ontologya true upper level ontologyno interference with domain ontologiesno interference with physics cognitionno abstractano negative entitiesexplicit treatment of instances types and relations
34
Three dichotomies
instance vs type
continuant vs occurrent
dependent vs independent
everything in the ontology is a type
types exist in reality through their instances
35
instance vs type
experiments as instances
experiments as types
ontologies relate to types (kinds universals)
we need to keep track of instances in databases
36
BFO
ContinuantOccurrent(Process)
IndependentContinuant
DependentContinuant
37
BFO
ContinuantOccurrent(Process)
IndependentContinuant
(molecule cell organorganism)
DependentContinuant
(quality functiondisease)
Functioning Side-Effect Stochastic Process
38
BFO
ContinuantOccurrent(Process)
IndependentContinuant
(molecule cell organorganism)
PATO Functioning Side-Effect Stochastic Process
39
Unifying goal integration
Integrating datandash within and across these domainsndash across levels of granularityndash across different perspectives
Requiresndash Rigorous formal definitions in both ontologies
and annotation schemas
40
Some thoughts on the ontology itself
Outlinendash Definitions
bull how do we define PATO termsbull what exactly is it wersquore defining
ndash is_a hierarchybull what are the top-level distinctionsbull what are the finer grained distinctions
ndash shapes and colors
41
Itrsquos all about the definitions
OBO Foundry Principlendash Definitions should describe things in reality
not how terms are usedbull definitions should not use the word lsquodescribingrsquo
Scope of PATO = Phenotypic qualities
42
Old PATOEntity ndash Attribute ndash Value
Eye ndash Red ndash Dark
New PATOEntity ndash Quality
Eye ndash Red Eye ndash Dark Red
Dark Red is_a Red
43
What a quality is NOT
Qualities are not measurementsndash Instances of qualities exist independently of their
measurementsndash Qualities can have zero or more measurements
These are not the names of qualitiesndash percentagendash processndash abnormalndash high
44
Some examples of qualities
The particular redness of the left eye of a single individual flyndash An instance of a quality type
The color lsquoredrsquondash A quality type
Note the eye does not instantiate lsquoredrsquo
PATO represents quality types (universals)ndash PATO definitions can be used to classify quality
instances by the types they instantiate
45
the particular case ofredness (of a particularfly eye)
the type ldquoredrdquo
instantiates
an instance of an eye(in a particular fly)
the type ldquoeyerdquo
instantiates
inheresin (is aquality ofhas_bearer)
46
Qualities are dependent entities
Qualities require bearersndash Bearers can be physical objects or processes
Examplendash A shape requires a physical object to bear itndash If the physical object ceases to exist (eg it
decomposes) then the shape ceases to exist
48
Scale Bearer Quality Definition (proposed)
Physical Continuant Mass Equivalent to the sum of the mass of the parts of the bearer (mass at the particle level is primitiveoutwith PATO)
Physical Continuant Opacity An optical quality manifest by the capacity of the bearer to block light
PhysChem Liquid Concentration A compositional relational quality manifest by the relative quantity of some chemical type contained by the bearer
Molecular Gene splicing quality manifest by the splicing processes undergone by the bearer
Cellular Cell ploidy A cellular quality manifest by the number of genomes that are part of the bearer
Cellular Cell transformative potency
A cellular quality manifest by the capacity of the bearer cell to differentiate to different cell types
Organismal Tissue tone
Organismal Organism reproductive quality
49
How many types of shape are there
notched T-shaped Y-shaped branched unbranched antrose retrose curled curved wiggly squiggly round flat square oblong elliptical ovoid cuboid spherical egg-shaped rod-shaped heart-shaped hellip
How do we define them
How do we compare them
Shapes cannot be organized in a linear scale
Compare problem of classifying RNA structures
50
Standard case monadic qualitiesExamples
ndash E=kidney Q=hypertrophiedndash autodef a kidney which is hypertrophied
We assume that there is more contextual data (not shown)ndash eg genotype environment number of organisms
in study that showed phenotype
Interpretation (with the rest of the database record)ndash all fish in this experiment with a particular
genotype had a hypertrophied kidney at some point in time
51
Who should use PATO
Originallyndash model organism mutant phenotypes
But alsondash ontology-based evolutionary systematicsndash neuroscience BIRNndash clinical uses
bull OMIMbull clinical records (clinical manifestations)bull drug effects chemical effects
ndash to define terms in other ontologiesbull eg diploid cell invasive tumor engineered gene
condensed chromosome
- The Ontology of Experiments + PATO
- Plan
- EXPO
- Slide 4
- EXPO Formalisation of Science
- Slide 6
- Slide 7
- Slide 8
- Suggested Upper Merged Ontology
- SUMO top level
- Suggested Upper Merged Ontology
- SUMO Structure
- SUMO+Domain Ontology
- Slide 14
- Slide 15
- advantages of SUMO
- problems with SUMO as Upper-Level
- Slide 18
- Slide 19
- Slide 20
- Slide 21
- OBI
- Overview of the Ontology of Biomedical Investigations
- OBI neacutee FuGO
- Motivation for OBI
- Emerging FuGO Design Principles
- OBI Collaborating Communities
- Slide 28
- Slide 29
- FuGO - Top Level Universals
- Slide 31
- Slide 32
- Basic Formal Ontology
- Three dichotomies
- instance vs type
- BFO
- Slide 37
- Slide 38
- Unifying goal integration
- Some thoughts on the ontology itself
- Itrsquos all about the definitions
- Old PATO Entity ndash Attribute ndash Value Eye ndash Red ndash Dark
- What a quality is NOT
- Some examples of qualities
- Slide 45
- Qualities are dependent entities
- Slide 48
- How many types of shape are there
- Standard case monadic qualities
- Who should use PATO
-
22
OBI
The Ontology of Biomedical Investigations
grew out of FuGE FuGO MGED PSI development activities
23
Overview of the Ontology of Biomedical Investigations
with thanks to Trish Whetzel (FuGO Working Group)
24
OBI neacutee FuGOPurpose
Provide a resource for the unambiguous description of the components of biomedical investigations such as the design protocols and instrumentation material data and types of analysis and statistical tools applied to the data NOT designed to model biology
Enables consistent annotation of data across different
technological and biological domains powerful queries semantically-driven data integration
25
Motivation for OBI
Standardization efforts in biological and technological domains Standard syntax - Data exchange formats
To provide a mechanism for software interoperability eg FuGE Object Model
Standard semantics - Controlled vocabularies or ontology Centralize commonalities for annotation term
needs across domains to describe an investigationstudyexperiment eg FuGO
26
Emerging FuGO Design Principles
OBO Foundry ontology utilize ontology best practices Inherit top level classes from an Upper Level ontology Use of the Relation Ontology Follow additional OBO Foundry principles Facilitates interoperability with other OBO Foundry
ontologiesOpen source approach
ProteacutegeacuteOWL Weekly conference calls Shared environment using Sourceforge (SF) and SF
mailing lists
27
OBI Collaborating CommunitiesCrop sciences Generation Challenge Programme (GCP)Environmental genomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiGenomic Standards Consortium (GSC)
wwwgenomicscehacukgenomecatalogueHUPO Proteomics Standards Initiative (PSI) psidevsourceforgenetImmunology Database and Analysis Portal wwwimmportorgImmune Epitope Database and Analysis Resource (IEDB)
httpwwwimmuneepitopeorghomedoInternational Society for Analytical Cytology httpwwwisac-netorgMetabolomics Standards Initiative (MSI) Neurogenetics Biomedical Informatics Research Network (BIRN)Nutrigenomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiPolymorphismToxicogenomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiTranscriptomics MGED Ontology Group
28
29
30
FuGO - Top Level Universals Continuant an entity that endureremains the same through time
bull Dependent Continuant depend on another entityEg Environment (depend on the set of ranges of conditions eg geographic location)
Eg Characteristics (entity that can be measured eg temperature unit)
- Realizable an entity that is realizable through a process (executedrun)Eg Software (a set of machine instructions)
Eg Design (the plan that can be realized in a process)
Eg Role (the part played by an entity within the context of a process)
bull Independent Continuant stands on its ownEg All physical entity (instrument technology platform document etc)
Eg Biological material (organism population etc)
Occurrent an entity that occursunfold in timebull Eg Temporal Regions Spatio-Temporal Regions (single actions or Event)
bull Process Eg Investigation (the entire lsquoexperimentalrsquo process)Eg Study (process of acquiring and treating the biological material)Eg Assay (process of performing some tests and recording the results)
31
32
33
Basic Formal Ontologya true upper level ontologyno interference with domain ontologiesno interference with physics cognitionno abstractano negative entitiesexplicit treatment of instances types and relations
34
Three dichotomies
instance vs type
continuant vs occurrent
dependent vs independent
everything in the ontology is a type
types exist in reality through their instances
35
instance vs type
experiments as instances
experiments as types
ontologies relate to types (kinds universals)
we need to keep track of instances in databases
36
BFO
ContinuantOccurrent(Process)
IndependentContinuant
DependentContinuant
37
BFO
ContinuantOccurrent(Process)
IndependentContinuant
(molecule cell organorganism)
DependentContinuant
(quality functiondisease)
Functioning Side-Effect Stochastic Process
38
BFO
ContinuantOccurrent(Process)
IndependentContinuant
(molecule cell organorganism)
PATO Functioning Side-Effect Stochastic Process
39
Unifying goal integration
Integrating datandash within and across these domainsndash across levels of granularityndash across different perspectives
Requiresndash Rigorous formal definitions in both ontologies
and annotation schemas
40
Some thoughts on the ontology itself
Outlinendash Definitions
bull how do we define PATO termsbull what exactly is it wersquore defining
ndash is_a hierarchybull what are the top-level distinctionsbull what are the finer grained distinctions
ndash shapes and colors
41
Itrsquos all about the definitions
OBO Foundry Principlendash Definitions should describe things in reality
not how terms are usedbull definitions should not use the word lsquodescribingrsquo
Scope of PATO = Phenotypic qualities
42
Old PATOEntity ndash Attribute ndash Value
Eye ndash Red ndash Dark
New PATOEntity ndash Quality
Eye ndash Red Eye ndash Dark Red
Dark Red is_a Red
43
What a quality is NOT
Qualities are not measurementsndash Instances of qualities exist independently of their
measurementsndash Qualities can have zero or more measurements
These are not the names of qualitiesndash percentagendash processndash abnormalndash high
44
Some examples of qualities
The particular redness of the left eye of a single individual flyndash An instance of a quality type
The color lsquoredrsquondash A quality type
Note the eye does not instantiate lsquoredrsquo
PATO represents quality types (universals)ndash PATO definitions can be used to classify quality
instances by the types they instantiate
45
the particular case ofredness (of a particularfly eye)
the type ldquoredrdquo
instantiates
an instance of an eye(in a particular fly)
the type ldquoeyerdquo
instantiates
inheresin (is aquality ofhas_bearer)
46
Qualities are dependent entities
Qualities require bearersndash Bearers can be physical objects or processes
Examplendash A shape requires a physical object to bear itndash If the physical object ceases to exist (eg it
decomposes) then the shape ceases to exist
48
Scale Bearer Quality Definition (proposed)
Physical Continuant Mass Equivalent to the sum of the mass of the parts of the bearer (mass at the particle level is primitiveoutwith PATO)
Physical Continuant Opacity An optical quality manifest by the capacity of the bearer to block light
PhysChem Liquid Concentration A compositional relational quality manifest by the relative quantity of some chemical type contained by the bearer
Molecular Gene splicing quality manifest by the splicing processes undergone by the bearer
Cellular Cell ploidy A cellular quality manifest by the number of genomes that are part of the bearer
Cellular Cell transformative potency
A cellular quality manifest by the capacity of the bearer cell to differentiate to different cell types
Organismal Tissue tone
Organismal Organism reproductive quality
49
How many types of shape are there
notched T-shaped Y-shaped branched unbranched antrose retrose curled curved wiggly squiggly round flat square oblong elliptical ovoid cuboid spherical egg-shaped rod-shaped heart-shaped hellip
How do we define them
How do we compare them
Shapes cannot be organized in a linear scale
Compare problem of classifying RNA structures
50
Standard case monadic qualitiesExamples
ndash E=kidney Q=hypertrophiedndash autodef a kidney which is hypertrophied
We assume that there is more contextual data (not shown)ndash eg genotype environment number of organisms
in study that showed phenotype
Interpretation (with the rest of the database record)ndash all fish in this experiment with a particular
genotype had a hypertrophied kidney at some point in time
51
Who should use PATO
Originallyndash model organism mutant phenotypes
But alsondash ontology-based evolutionary systematicsndash neuroscience BIRNndash clinical uses
bull OMIMbull clinical records (clinical manifestations)bull drug effects chemical effects
ndash to define terms in other ontologiesbull eg diploid cell invasive tumor engineered gene
condensed chromosome
- The Ontology of Experiments + PATO
- Plan
- EXPO
- Slide 4
- EXPO Formalisation of Science
- Slide 6
- Slide 7
- Slide 8
- Suggested Upper Merged Ontology
- SUMO top level
- Suggested Upper Merged Ontology
- SUMO Structure
- SUMO+Domain Ontology
- Slide 14
- Slide 15
- advantages of SUMO
- problems with SUMO as Upper-Level
- Slide 18
- Slide 19
- Slide 20
- Slide 21
- OBI
- Overview of the Ontology of Biomedical Investigations
- OBI neacutee FuGO
- Motivation for OBI
- Emerging FuGO Design Principles
- OBI Collaborating Communities
- Slide 28
- Slide 29
- FuGO - Top Level Universals
- Slide 31
- Slide 32
- Basic Formal Ontology
- Three dichotomies
- instance vs type
- BFO
- Slide 37
- Slide 38
- Unifying goal integration
- Some thoughts on the ontology itself
- Itrsquos all about the definitions
- Old PATO Entity ndash Attribute ndash Value Eye ndash Red ndash Dark
- What a quality is NOT
- Some examples of qualities
- Slide 45
- Qualities are dependent entities
- Slide 48
- How many types of shape are there
- Standard case monadic qualities
- Who should use PATO
-
23
Overview of the Ontology of Biomedical Investigations
with thanks to Trish Whetzel (FuGO Working Group)
24
OBI neacutee FuGOPurpose
Provide a resource for the unambiguous description of the components of biomedical investigations such as the design protocols and instrumentation material data and types of analysis and statistical tools applied to the data NOT designed to model biology
Enables consistent annotation of data across different
technological and biological domains powerful queries semantically-driven data integration
25
Motivation for OBI
Standardization efforts in biological and technological domains Standard syntax - Data exchange formats
To provide a mechanism for software interoperability eg FuGE Object Model
Standard semantics - Controlled vocabularies or ontology Centralize commonalities for annotation term
needs across domains to describe an investigationstudyexperiment eg FuGO
26
Emerging FuGO Design Principles
OBO Foundry ontology utilize ontology best practices Inherit top level classes from an Upper Level ontology Use of the Relation Ontology Follow additional OBO Foundry principles Facilitates interoperability with other OBO Foundry
ontologiesOpen source approach
ProteacutegeacuteOWL Weekly conference calls Shared environment using Sourceforge (SF) and SF
mailing lists
27
OBI Collaborating CommunitiesCrop sciences Generation Challenge Programme (GCP)Environmental genomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiGenomic Standards Consortium (GSC)
wwwgenomicscehacukgenomecatalogueHUPO Proteomics Standards Initiative (PSI) psidevsourceforgenetImmunology Database and Analysis Portal wwwimmportorgImmune Epitope Database and Analysis Resource (IEDB)
httpwwwimmuneepitopeorghomedoInternational Society for Analytical Cytology httpwwwisac-netorgMetabolomics Standards Initiative (MSI) Neurogenetics Biomedical Informatics Research Network (BIRN)Nutrigenomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiPolymorphismToxicogenomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiTranscriptomics MGED Ontology Group
28
29
30
FuGO - Top Level Universals Continuant an entity that endureremains the same through time
bull Dependent Continuant depend on another entityEg Environment (depend on the set of ranges of conditions eg geographic location)
Eg Characteristics (entity that can be measured eg temperature unit)
- Realizable an entity that is realizable through a process (executedrun)Eg Software (a set of machine instructions)
Eg Design (the plan that can be realized in a process)
Eg Role (the part played by an entity within the context of a process)
bull Independent Continuant stands on its ownEg All physical entity (instrument technology platform document etc)
Eg Biological material (organism population etc)
Occurrent an entity that occursunfold in timebull Eg Temporal Regions Spatio-Temporal Regions (single actions or Event)
bull Process Eg Investigation (the entire lsquoexperimentalrsquo process)Eg Study (process of acquiring and treating the biological material)Eg Assay (process of performing some tests and recording the results)
31
32
33
Basic Formal Ontologya true upper level ontologyno interference with domain ontologiesno interference with physics cognitionno abstractano negative entitiesexplicit treatment of instances types and relations
34
Three dichotomies
instance vs type
continuant vs occurrent
dependent vs independent
everything in the ontology is a type
types exist in reality through their instances
35
instance vs type
experiments as instances
experiments as types
ontologies relate to types (kinds universals)
we need to keep track of instances in databases
36
BFO
ContinuantOccurrent(Process)
IndependentContinuant
DependentContinuant
37
BFO
ContinuantOccurrent(Process)
IndependentContinuant
(molecule cell organorganism)
DependentContinuant
(quality functiondisease)
Functioning Side-Effect Stochastic Process
38
BFO
ContinuantOccurrent(Process)
IndependentContinuant
(molecule cell organorganism)
PATO Functioning Side-Effect Stochastic Process
39
Unifying goal integration
Integrating datandash within and across these domainsndash across levels of granularityndash across different perspectives
Requiresndash Rigorous formal definitions in both ontologies
and annotation schemas
40
Some thoughts on the ontology itself
Outlinendash Definitions
bull how do we define PATO termsbull what exactly is it wersquore defining
ndash is_a hierarchybull what are the top-level distinctionsbull what are the finer grained distinctions
ndash shapes and colors
41
Itrsquos all about the definitions
OBO Foundry Principlendash Definitions should describe things in reality
not how terms are usedbull definitions should not use the word lsquodescribingrsquo
Scope of PATO = Phenotypic qualities
42
Old PATOEntity ndash Attribute ndash Value
Eye ndash Red ndash Dark
New PATOEntity ndash Quality
Eye ndash Red Eye ndash Dark Red
Dark Red is_a Red
43
What a quality is NOT
Qualities are not measurementsndash Instances of qualities exist independently of their
measurementsndash Qualities can have zero or more measurements
These are not the names of qualitiesndash percentagendash processndash abnormalndash high
44
Some examples of qualities
The particular redness of the left eye of a single individual flyndash An instance of a quality type
The color lsquoredrsquondash A quality type
Note the eye does not instantiate lsquoredrsquo
PATO represents quality types (universals)ndash PATO definitions can be used to classify quality
instances by the types they instantiate
45
the particular case ofredness (of a particularfly eye)
the type ldquoredrdquo
instantiates
an instance of an eye(in a particular fly)
the type ldquoeyerdquo
instantiates
inheresin (is aquality ofhas_bearer)
46
Qualities are dependent entities
Qualities require bearersndash Bearers can be physical objects or processes
Examplendash A shape requires a physical object to bear itndash If the physical object ceases to exist (eg it
decomposes) then the shape ceases to exist
48
Scale Bearer Quality Definition (proposed)
Physical Continuant Mass Equivalent to the sum of the mass of the parts of the bearer (mass at the particle level is primitiveoutwith PATO)
Physical Continuant Opacity An optical quality manifest by the capacity of the bearer to block light
PhysChem Liquid Concentration A compositional relational quality manifest by the relative quantity of some chemical type contained by the bearer
Molecular Gene splicing quality manifest by the splicing processes undergone by the bearer
Cellular Cell ploidy A cellular quality manifest by the number of genomes that are part of the bearer
Cellular Cell transformative potency
A cellular quality manifest by the capacity of the bearer cell to differentiate to different cell types
Organismal Tissue tone
Organismal Organism reproductive quality
49
How many types of shape are there
notched T-shaped Y-shaped branched unbranched antrose retrose curled curved wiggly squiggly round flat square oblong elliptical ovoid cuboid spherical egg-shaped rod-shaped heart-shaped hellip
How do we define them
How do we compare them
Shapes cannot be organized in a linear scale
Compare problem of classifying RNA structures
50
Standard case monadic qualitiesExamples
ndash E=kidney Q=hypertrophiedndash autodef a kidney which is hypertrophied
We assume that there is more contextual data (not shown)ndash eg genotype environment number of organisms
in study that showed phenotype
Interpretation (with the rest of the database record)ndash all fish in this experiment with a particular
genotype had a hypertrophied kidney at some point in time
51
Who should use PATO
Originallyndash model organism mutant phenotypes
But alsondash ontology-based evolutionary systematicsndash neuroscience BIRNndash clinical uses
bull OMIMbull clinical records (clinical manifestations)bull drug effects chemical effects
ndash to define terms in other ontologiesbull eg diploid cell invasive tumor engineered gene
condensed chromosome
- The Ontology of Experiments + PATO
- Plan
- EXPO
- Slide 4
- EXPO Formalisation of Science
- Slide 6
- Slide 7
- Slide 8
- Suggested Upper Merged Ontology
- SUMO top level
- Suggested Upper Merged Ontology
- SUMO Structure
- SUMO+Domain Ontology
- Slide 14
- Slide 15
- advantages of SUMO
- problems with SUMO as Upper-Level
- Slide 18
- Slide 19
- Slide 20
- Slide 21
- OBI
- Overview of the Ontology of Biomedical Investigations
- OBI neacutee FuGO
- Motivation for OBI
- Emerging FuGO Design Principles
- OBI Collaborating Communities
- Slide 28
- Slide 29
- FuGO - Top Level Universals
- Slide 31
- Slide 32
- Basic Formal Ontology
- Three dichotomies
- instance vs type
- BFO
- Slide 37
- Slide 38
- Unifying goal integration
- Some thoughts on the ontology itself
- Itrsquos all about the definitions
- Old PATO Entity ndash Attribute ndash Value Eye ndash Red ndash Dark
- What a quality is NOT
- Some examples of qualities
- Slide 45
- Qualities are dependent entities
- Slide 48
- How many types of shape are there
- Standard case monadic qualities
- Who should use PATO
-
24
OBI neacutee FuGOPurpose
Provide a resource for the unambiguous description of the components of biomedical investigations such as the design protocols and instrumentation material data and types of analysis and statistical tools applied to the data NOT designed to model biology
Enables consistent annotation of data across different
technological and biological domains powerful queries semantically-driven data integration
25
Motivation for OBI
Standardization efforts in biological and technological domains Standard syntax - Data exchange formats
To provide a mechanism for software interoperability eg FuGE Object Model
Standard semantics - Controlled vocabularies or ontology Centralize commonalities for annotation term
needs across domains to describe an investigationstudyexperiment eg FuGO
26
Emerging FuGO Design Principles
OBO Foundry ontology utilize ontology best practices Inherit top level classes from an Upper Level ontology Use of the Relation Ontology Follow additional OBO Foundry principles Facilitates interoperability with other OBO Foundry
ontologiesOpen source approach
ProteacutegeacuteOWL Weekly conference calls Shared environment using Sourceforge (SF) and SF
mailing lists
27
OBI Collaborating CommunitiesCrop sciences Generation Challenge Programme (GCP)Environmental genomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiGenomic Standards Consortium (GSC)
wwwgenomicscehacukgenomecatalogueHUPO Proteomics Standards Initiative (PSI) psidevsourceforgenetImmunology Database and Analysis Portal wwwimmportorgImmune Epitope Database and Analysis Resource (IEDB)
httpwwwimmuneepitopeorghomedoInternational Society for Analytical Cytology httpwwwisac-netorgMetabolomics Standards Initiative (MSI) Neurogenetics Biomedical Informatics Research Network (BIRN)Nutrigenomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiPolymorphismToxicogenomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiTranscriptomics MGED Ontology Group
28
29
30
FuGO - Top Level Universals Continuant an entity that endureremains the same through time
bull Dependent Continuant depend on another entityEg Environment (depend on the set of ranges of conditions eg geographic location)
Eg Characteristics (entity that can be measured eg temperature unit)
- Realizable an entity that is realizable through a process (executedrun)Eg Software (a set of machine instructions)
Eg Design (the plan that can be realized in a process)
Eg Role (the part played by an entity within the context of a process)
bull Independent Continuant stands on its ownEg All physical entity (instrument technology platform document etc)
Eg Biological material (organism population etc)
Occurrent an entity that occursunfold in timebull Eg Temporal Regions Spatio-Temporal Regions (single actions or Event)
bull Process Eg Investigation (the entire lsquoexperimentalrsquo process)Eg Study (process of acquiring and treating the biological material)Eg Assay (process of performing some tests and recording the results)
31
32
33
Basic Formal Ontologya true upper level ontologyno interference with domain ontologiesno interference with physics cognitionno abstractano negative entitiesexplicit treatment of instances types and relations
34
Three dichotomies
instance vs type
continuant vs occurrent
dependent vs independent
everything in the ontology is a type
types exist in reality through their instances
35
instance vs type
experiments as instances
experiments as types
ontologies relate to types (kinds universals)
we need to keep track of instances in databases
36
BFO
ContinuantOccurrent(Process)
IndependentContinuant
DependentContinuant
37
BFO
ContinuantOccurrent(Process)
IndependentContinuant
(molecule cell organorganism)
DependentContinuant
(quality functiondisease)
Functioning Side-Effect Stochastic Process
38
BFO
ContinuantOccurrent(Process)
IndependentContinuant
(molecule cell organorganism)
PATO Functioning Side-Effect Stochastic Process
39
Unifying goal integration
Integrating datandash within and across these domainsndash across levels of granularityndash across different perspectives
Requiresndash Rigorous formal definitions in both ontologies
and annotation schemas
40
Some thoughts on the ontology itself
Outlinendash Definitions
bull how do we define PATO termsbull what exactly is it wersquore defining
ndash is_a hierarchybull what are the top-level distinctionsbull what are the finer grained distinctions
ndash shapes and colors
41
Itrsquos all about the definitions
OBO Foundry Principlendash Definitions should describe things in reality
not how terms are usedbull definitions should not use the word lsquodescribingrsquo
Scope of PATO = Phenotypic qualities
42
Old PATOEntity ndash Attribute ndash Value
Eye ndash Red ndash Dark
New PATOEntity ndash Quality
Eye ndash Red Eye ndash Dark Red
Dark Red is_a Red
43
What a quality is NOT
Qualities are not measurementsndash Instances of qualities exist independently of their
measurementsndash Qualities can have zero or more measurements
These are not the names of qualitiesndash percentagendash processndash abnormalndash high
44
Some examples of qualities
The particular redness of the left eye of a single individual flyndash An instance of a quality type
The color lsquoredrsquondash A quality type
Note the eye does not instantiate lsquoredrsquo
PATO represents quality types (universals)ndash PATO definitions can be used to classify quality
instances by the types they instantiate
45
the particular case ofredness (of a particularfly eye)
the type ldquoredrdquo
instantiates
an instance of an eye(in a particular fly)
the type ldquoeyerdquo
instantiates
inheresin (is aquality ofhas_bearer)
46
Qualities are dependent entities
Qualities require bearersndash Bearers can be physical objects or processes
Examplendash A shape requires a physical object to bear itndash If the physical object ceases to exist (eg it
decomposes) then the shape ceases to exist
48
Scale Bearer Quality Definition (proposed)
Physical Continuant Mass Equivalent to the sum of the mass of the parts of the bearer (mass at the particle level is primitiveoutwith PATO)
Physical Continuant Opacity An optical quality manifest by the capacity of the bearer to block light
PhysChem Liquid Concentration A compositional relational quality manifest by the relative quantity of some chemical type contained by the bearer
Molecular Gene splicing quality manifest by the splicing processes undergone by the bearer
Cellular Cell ploidy A cellular quality manifest by the number of genomes that are part of the bearer
Cellular Cell transformative potency
A cellular quality manifest by the capacity of the bearer cell to differentiate to different cell types
Organismal Tissue tone
Organismal Organism reproductive quality
49
How many types of shape are there
notched T-shaped Y-shaped branched unbranched antrose retrose curled curved wiggly squiggly round flat square oblong elliptical ovoid cuboid spherical egg-shaped rod-shaped heart-shaped hellip
How do we define them
How do we compare them
Shapes cannot be organized in a linear scale
Compare problem of classifying RNA structures
50
Standard case monadic qualitiesExamples
ndash E=kidney Q=hypertrophiedndash autodef a kidney which is hypertrophied
We assume that there is more contextual data (not shown)ndash eg genotype environment number of organisms
in study that showed phenotype
Interpretation (with the rest of the database record)ndash all fish in this experiment with a particular
genotype had a hypertrophied kidney at some point in time
51
Who should use PATO
Originallyndash model organism mutant phenotypes
But alsondash ontology-based evolutionary systematicsndash neuroscience BIRNndash clinical uses
bull OMIMbull clinical records (clinical manifestations)bull drug effects chemical effects
ndash to define terms in other ontologiesbull eg diploid cell invasive tumor engineered gene
condensed chromosome
- The Ontology of Experiments + PATO
- Plan
- EXPO
- Slide 4
- EXPO Formalisation of Science
- Slide 6
- Slide 7
- Slide 8
- Suggested Upper Merged Ontology
- SUMO top level
- Suggested Upper Merged Ontology
- SUMO Structure
- SUMO+Domain Ontology
- Slide 14
- Slide 15
- advantages of SUMO
- problems with SUMO as Upper-Level
- Slide 18
- Slide 19
- Slide 20
- Slide 21
- OBI
- Overview of the Ontology of Biomedical Investigations
- OBI neacutee FuGO
- Motivation for OBI
- Emerging FuGO Design Principles
- OBI Collaborating Communities
- Slide 28
- Slide 29
- FuGO - Top Level Universals
- Slide 31
- Slide 32
- Basic Formal Ontology
- Three dichotomies
- instance vs type
- BFO
- Slide 37
- Slide 38
- Unifying goal integration
- Some thoughts on the ontology itself
- Itrsquos all about the definitions
- Old PATO Entity ndash Attribute ndash Value Eye ndash Red ndash Dark
- What a quality is NOT
- Some examples of qualities
- Slide 45
- Qualities are dependent entities
- Slide 48
- How many types of shape are there
- Standard case monadic qualities
- Who should use PATO
-
25
Motivation for OBI
Standardization efforts in biological and technological domains Standard syntax - Data exchange formats
To provide a mechanism for software interoperability eg FuGE Object Model
Standard semantics - Controlled vocabularies or ontology Centralize commonalities for annotation term
needs across domains to describe an investigationstudyexperiment eg FuGO
26
Emerging FuGO Design Principles
OBO Foundry ontology utilize ontology best practices Inherit top level classes from an Upper Level ontology Use of the Relation Ontology Follow additional OBO Foundry principles Facilitates interoperability with other OBO Foundry
ontologiesOpen source approach
ProteacutegeacuteOWL Weekly conference calls Shared environment using Sourceforge (SF) and SF
mailing lists
27
OBI Collaborating CommunitiesCrop sciences Generation Challenge Programme (GCP)Environmental genomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiGenomic Standards Consortium (GSC)
wwwgenomicscehacukgenomecatalogueHUPO Proteomics Standards Initiative (PSI) psidevsourceforgenetImmunology Database and Analysis Portal wwwimmportorgImmune Epitope Database and Analysis Resource (IEDB)
httpwwwimmuneepitopeorghomedoInternational Society for Analytical Cytology httpwwwisac-netorgMetabolomics Standards Initiative (MSI) Neurogenetics Biomedical Informatics Research Network (BIRN)Nutrigenomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiPolymorphismToxicogenomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiTranscriptomics MGED Ontology Group
28
29
30
FuGO - Top Level Universals Continuant an entity that endureremains the same through time
bull Dependent Continuant depend on another entityEg Environment (depend on the set of ranges of conditions eg geographic location)
Eg Characteristics (entity that can be measured eg temperature unit)
- Realizable an entity that is realizable through a process (executedrun)Eg Software (a set of machine instructions)
Eg Design (the plan that can be realized in a process)
Eg Role (the part played by an entity within the context of a process)
bull Independent Continuant stands on its ownEg All physical entity (instrument technology platform document etc)
Eg Biological material (organism population etc)
Occurrent an entity that occursunfold in timebull Eg Temporal Regions Spatio-Temporal Regions (single actions or Event)
bull Process Eg Investigation (the entire lsquoexperimentalrsquo process)Eg Study (process of acquiring and treating the biological material)Eg Assay (process of performing some tests and recording the results)
31
32
33
Basic Formal Ontologya true upper level ontologyno interference with domain ontologiesno interference with physics cognitionno abstractano negative entitiesexplicit treatment of instances types and relations
34
Three dichotomies
instance vs type
continuant vs occurrent
dependent vs independent
everything in the ontology is a type
types exist in reality through their instances
35
instance vs type
experiments as instances
experiments as types
ontologies relate to types (kinds universals)
we need to keep track of instances in databases
36
BFO
ContinuantOccurrent(Process)
IndependentContinuant
DependentContinuant
37
BFO
ContinuantOccurrent(Process)
IndependentContinuant
(molecule cell organorganism)
DependentContinuant
(quality functiondisease)
Functioning Side-Effect Stochastic Process
38
BFO
ContinuantOccurrent(Process)
IndependentContinuant
(molecule cell organorganism)
PATO Functioning Side-Effect Stochastic Process
39
Unifying goal integration
Integrating datandash within and across these domainsndash across levels of granularityndash across different perspectives
Requiresndash Rigorous formal definitions in both ontologies
and annotation schemas
40
Some thoughts on the ontology itself
Outlinendash Definitions
bull how do we define PATO termsbull what exactly is it wersquore defining
ndash is_a hierarchybull what are the top-level distinctionsbull what are the finer grained distinctions
ndash shapes and colors
41
Itrsquos all about the definitions
OBO Foundry Principlendash Definitions should describe things in reality
not how terms are usedbull definitions should not use the word lsquodescribingrsquo
Scope of PATO = Phenotypic qualities
42
Old PATOEntity ndash Attribute ndash Value
Eye ndash Red ndash Dark
New PATOEntity ndash Quality
Eye ndash Red Eye ndash Dark Red
Dark Red is_a Red
43
What a quality is NOT
Qualities are not measurementsndash Instances of qualities exist independently of their
measurementsndash Qualities can have zero or more measurements
These are not the names of qualitiesndash percentagendash processndash abnormalndash high
44
Some examples of qualities
The particular redness of the left eye of a single individual flyndash An instance of a quality type
The color lsquoredrsquondash A quality type
Note the eye does not instantiate lsquoredrsquo
PATO represents quality types (universals)ndash PATO definitions can be used to classify quality
instances by the types they instantiate
45
the particular case ofredness (of a particularfly eye)
the type ldquoredrdquo
instantiates
an instance of an eye(in a particular fly)
the type ldquoeyerdquo
instantiates
inheresin (is aquality ofhas_bearer)
46
Qualities are dependent entities
Qualities require bearersndash Bearers can be physical objects or processes
Examplendash A shape requires a physical object to bear itndash If the physical object ceases to exist (eg it
decomposes) then the shape ceases to exist
48
Scale Bearer Quality Definition (proposed)
Physical Continuant Mass Equivalent to the sum of the mass of the parts of the bearer (mass at the particle level is primitiveoutwith PATO)
Physical Continuant Opacity An optical quality manifest by the capacity of the bearer to block light
PhysChem Liquid Concentration A compositional relational quality manifest by the relative quantity of some chemical type contained by the bearer
Molecular Gene splicing quality manifest by the splicing processes undergone by the bearer
Cellular Cell ploidy A cellular quality manifest by the number of genomes that are part of the bearer
Cellular Cell transformative potency
A cellular quality manifest by the capacity of the bearer cell to differentiate to different cell types
Organismal Tissue tone
Organismal Organism reproductive quality
49
How many types of shape are there
notched T-shaped Y-shaped branched unbranched antrose retrose curled curved wiggly squiggly round flat square oblong elliptical ovoid cuboid spherical egg-shaped rod-shaped heart-shaped hellip
How do we define them
How do we compare them
Shapes cannot be organized in a linear scale
Compare problem of classifying RNA structures
50
Standard case monadic qualitiesExamples
ndash E=kidney Q=hypertrophiedndash autodef a kidney which is hypertrophied
We assume that there is more contextual data (not shown)ndash eg genotype environment number of organisms
in study that showed phenotype
Interpretation (with the rest of the database record)ndash all fish in this experiment with a particular
genotype had a hypertrophied kidney at some point in time
51
Who should use PATO
Originallyndash model organism mutant phenotypes
But alsondash ontology-based evolutionary systematicsndash neuroscience BIRNndash clinical uses
bull OMIMbull clinical records (clinical manifestations)bull drug effects chemical effects
ndash to define terms in other ontologiesbull eg diploid cell invasive tumor engineered gene
condensed chromosome
- The Ontology of Experiments + PATO
- Plan
- EXPO
- Slide 4
- EXPO Formalisation of Science
- Slide 6
- Slide 7
- Slide 8
- Suggested Upper Merged Ontology
- SUMO top level
- Suggested Upper Merged Ontology
- SUMO Structure
- SUMO+Domain Ontology
- Slide 14
- Slide 15
- advantages of SUMO
- problems with SUMO as Upper-Level
- Slide 18
- Slide 19
- Slide 20
- Slide 21
- OBI
- Overview of the Ontology of Biomedical Investigations
- OBI neacutee FuGO
- Motivation for OBI
- Emerging FuGO Design Principles
- OBI Collaborating Communities
- Slide 28
- Slide 29
- FuGO - Top Level Universals
- Slide 31
- Slide 32
- Basic Formal Ontology
- Three dichotomies
- instance vs type
- BFO
- Slide 37
- Slide 38
- Unifying goal integration
- Some thoughts on the ontology itself
- Itrsquos all about the definitions
- Old PATO Entity ndash Attribute ndash Value Eye ndash Red ndash Dark
- What a quality is NOT
- Some examples of qualities
- Slide 45
- Qualities are dependent entities
- Slide 48
- How many types of shape are there
- Standard case monadic qualities
- Who should use PATO
-
26
Emerging FuGO Design Principles
OBO Foundry ontology utilize ontology best practices Inherit top level classes from an Upper Level ontology Use of the Relation Ontology Follow additional OBO Foundry principles Facilitates interoperability with other OBO Foundry
ontologiesOpen source approach
ProteacutegeacuteOWL Weekly conference calls Shared environment using Sourceforge (SF) and SF
mailing lists
27
OBI Collaborating CommunitiesCrop sciences Generation Challenge Programme (GCP)Environmental genomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiGenomic Standards Consortium (GSC)
wwwgenomicscehacukgenomecatalogueHUPO Proteomics Standards Initiative (PSI) psidevsourceforgenetImmunology Database and Analysis Portal wwwimmportorgImmune Epitope Database and Analysis Resource (IEDB)
httpwwwimmuneepitopeorghomedoInternational Society for Analytical Cytology httpwwwisac-netorgMetabolomics Standards Initiative (MSI) Neurogenetics Biomedical Informatics Research Network (BIRN)Nutrigenomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiPolymorphismToxicogenomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiTranscriptomics MGED Ontology Group
28
29
30
FuGO - Top Level Universals Continuant an entity that endureremains the same through time
bull Dependent Continuant depend on another entityEg Environment (depend on the set of ranges of conditions eg geographic location)
Eg Characteristics (entity that can be measured eg temperature unit)
- Realizable an entity that is realizable through a process (executedrun)Eg Software (a set of machine instructions)
Eg Design (the plan that can be realized in a process)
Eg Role (the part played by an entity within the context of a process)
bull Independent Continuant stands on its ownEg All physical entity (instrument technology platform document etc)
Eg Biological material (organism population etc)
Occurrent an entity that occursunfold in timebull Eg Temporal Regions Spatio-Temporal Regions (single actions or Event)
bull Process Eg Investigation (the entire lsquoexperimentalrsquo process)Eg Study (process of acquiring and treating the biological material)Eg Assay (process of performing some tests and recording the results)
31
32
33
Basic Formal Ontologya true upper level ontologyno interference with domain ontologiesno interference with physics cognitionno abstractano negative entitiesexplicit treatment of instances types and relations
34
Three dichotomies
instance vs type
continuant vs occurrent
dependent vs independent
everything in the ontology is a type
types exist in reality through their instances
35
instance vs type
experiments as instances
experiments as types
ontologies relate to types (kinds universals)
we need to keep track of instances in databases
36
BFO
ContinuantOccurrent(Process)
IndependentContinuant
DependentContinuant
37
BFO
ContinuantOccurrent(Process)
IndependentContinuant
(molecule cell organorganism)
DependentContinuant
(quality functiondisease)
Functioning Side-Effect Stochastic Process
38
BFO
ContinuantOccurrent(Process)
IndependentContinuant
(molecule cell organorganism)
PATO Functioning Side-Effect Stochastic Process
39
Unifying goal integration
Integrating datandash within and across these domainsndash across levels of granularityndash across different perspectives
Requiresndash Rigorous formal definitions in both ontologies
and annotation schemas
40
Some thoughts on the ontology itself
Outlinendash Definitions
bull how do we define PATO termsbull what exactly is it wersquore defining
ndash is_a hierarchybull what are the top-level distinctionsbull what are the finer grained distinctions
ndash shapes and colors
41
Itrsquos all about the definitions
OBO Foundry Principlendash Definitions should describe things in reality
not how terms are usedbull definitions should not use the word lsquodescribingrsquo
Scope of PATO = Phenotypic qualities
42
Old PATOEntity ndash Attribute ndash Value
Eye ndash Red ndash Dark
New PATOEntity ndash Quality
Eye ndash Red Eye ndash Dark Red
Dark Red is_a Red
43
What a quality is NOT
Qualities are not measurementsndash Instances of qualities exist independently of their
measurementsndash Qualities can have zero or more measurements
These are not the names of qualitiesndash percentagendash processndash abnormalndash high
44
Some examples of qualities
The particular redness of the left eye of a single individual flyndash An instance of a quality type
The color lsquoredrsquondash A quality type
Note the eye does not instantiate lsquoredrsquo
PATO represents quality types (universals)ndash PATO definitions can be used to classify quality
instances by the types they instantiate
45
the particular case ofredness (of a particularfly eye)
the type ldquoredrdquo
instantiates
an instance of an eye(in a particular fly)
the type ldquoeyerdquo
instantiates
inheresin (is aquality ofhas_bearer)
46
Qualities are dependent entities
Qualities require bearersndash Bearers can be physical objects or processes
Examplendash A shape requires a physical object to bear itndash If the physical object ceases to exist (eg it
decomposes) then the shape ceases to exist
48
Scale Bearer Quality Definition (proposed)
Physical Continuant Mass Equivalent to the sum of the mass of the parts of the bearer (mass at the particle level is primitiveoutwith PATO)
Physical Continuant Opacity An optical quality manifest by the capacity of the bearer to block light
PhysChem Liquid Concentration A compositional relational quality manifest by the relative quantity of some chemical type contained by the bearer
Molecular Gene splicing quality manifest by the splicing processes undergone by the bearer
Cellular Cell ploidy A cellular quality manifest by the number of genomes that are part of the bearer
Cellular Cell transformative potency
A cellular quality manifest by the capacity of the bearer cell to differentiate to different cell types
Organismal Tissue tone
Organismal Organism reproductive quality
49
How many types of shape are there
notched T-shaped Y-shaped branched unbranched antrose retrose curled curved wiggly squiggly round flat square oblong elliptical ovoid cuboid spherical egg-shaped rod-shaped heart-shaped hellip
How do we define them
How do we compare them
Shapes cannot be organized in a linear scale
Compare problem of classifying RNA structures
50
Standard case monadic qualitiesExamples
ndash E=kidney Q=hypertrophiedndash autodef a kidney which is hypertrophied
We assume that there is more contextual data (not shown)ndash eg genotype environment number of organisms
in study that showed phenotype
Interpretation (with the rest of the database record)ndash all fish in this experiment with a particular
genotype had a hypertrophied kidney at some point in time
51
Who should use PATO
Originallyndash model organism mutant phenotypes
But alsondash ontology-based evolutionary systematicsndash neuroscience BIRNndash clinical uses
bull OMIMbull clinical records (clinical manifestations)bull drug effects chemical effects
ndash to define terms in other ontologiesbull eg diploid cell invasive tumor engineered gene
condensed chromosome
- The Ontology of Experiments + PATO
- Plan
- EXPO
- Slide 4
- EXPO Formalisation of Science
- Slide 6
- Slide 7
- Slide 8
- Suggested Upper Merged Ontology
- SUMO top level
- Suggested Upper Merged Ontology
- SUMO Structure
- SUMO+Domain Ontology
- Slide 14
- Slide 15
- advantages of SUMO
- problems with SUMO as Upper-Level
- Slide 18
- Slide 19
- Slide 20
- Slide 21
- OBI
- Overview of the Ontology of Biomedical Investigations
- OBI neacutee FuGO
- Motivation for OBI
- Emerging FuGO Design Principles
- OBI Collaborating Communities
- Slide 28
- Slide 29
- FuGO - Top Level Universals
- Slide 31
- Slide 32
- Basic Formal Ontology
- Three dichotomies
- instance vs type
- BFO
- Slide 37
- Slide 38
- Unifying goal integration
- Some thoughts on the ontology itself
- Itrsquos all about the definitions
- Old PATO Entity ndash Attribute ndash Value Eye ndash Red ndash Dark
- What a quality is NOT
- Some examples of qualities
- Slide 45
- Qualities are dependent entities
- Slide 48
- How many types of shape are there
- Standard case monadic qualities
- Who should use PATO
-
27
OBI Collaborating CommunitiesCrop sciences Generation Challenge Programme (GCP)Environmental genomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiGenomic Standards Consortium (GSC)
wwwgenomicscehacukgenomecatalogueHUPO Proteomics Standards Initiative (PSI) psidevsourceforgenetImmunology Database and Analysis Portal wwwimmportorgImmune Epitope Database and Analysis Resource (IEDB)
httpwwwimmuneepitopeorghomedoInternational Society for Analytical Cytology httpwwwisac-netorgMetabolomics Standards Initiative (MSI) Neurogenetics Biomedical Informatics Research Network (BIRN)Nutrigenomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiPolymorphismToxicogenomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiTranscriptomics MGED Ontology Group
28
29
30
FuGO - Top Level Universals Continuant an entity that endureremains the same through time
bull Dependent Continuant depend on another entityEg Environment (depend on the set of ranges of conditions eg geographic location)
Eg Characteristics (entity that can be measured eg temperature unit)
- Realizable an entity that is realizable through a process (executedrun)Eg Software (a set of machine instructions)
Eg Design (the plan that can be realized in a process)
Eg Role (the part played by an entity within the context of a process)
bull Independent Continuant stands on its ownEg All physical entity (instrument technology platform document etc)
Eg Biological material (organism population etc)
Occurrent an entity that occursunfold in timebull Eg Temporal Regions Spatio-Temporal Regions (single actions or Event)
bull Process Eg Investigation (the entire lsquoexperimentalrsquo process)Eg Study (process of acquiring and treating the biological material)Eg Assay (process of performing some tests and recording the results)
31
32
33
Basic Formal Ontologya true upper level ontologyno interference with domain ontologiesno interference with physics cognitionno abstractano negative entitiesexplicit treatment of instances types and relations
34
Three dichotomies
instance vs type
continuant vs occurrent
dependent vs independent
everything in the ontology is a type
types exist in reality through their instances
35
instance vs type
experiments as instances
experiments as types
ontologies relate to types (kinds universals)
we need to keep track of instances in databases
36
BFO
ContinuantOccurrent(Process)
IndependentContinuant
DependentContinuant
37
BFO
ContinuantOccurrent(Process)
IndependentContinuant
(molecule cell organorganism)
DependentContinuant
(quality functiondisease)
Functioning Side-Effect Stochastic Process
38
BFO
ContinuantOccurrent(Process)
IndependentContinuant
(molecule cell organorganism)
PATO Functioning Side-Effect Stochastic Process
39
Unifying goal integration
Integrating datandash within and across these domainsndash across levels of granularityndash across different perspectives
Requiresndash Rigorous formal definitions in both ontologies
and annotation schemas
40
Some thoughts on the ontology itself
Outlinendash Definitions
bull how do we define PATO termsbull what exactly is it wersquore defining
ndash is_a hierarchybull what are the top-level distinctionsbull what are the finer grained distinctions
ndash shapes and colors
41
Itrsquos all about the definitions
OBO Foundry Principlendash Definitions should describe things in reality
not how terms are usedbull definitions should not use the word lsquodescribingrsquo
Scope of PATO = Phenotypic qualities
42
Old PATOEntity ndash Attribute ndash Value
Eye ndash Red ndash Dark
New PATOEntity ndash Quality
Eye ndash Red Eye ndash Dark Red
Dark Red is_a Red
43
What a quality is NOT
Qualities are not measurementsndash Instances of qualities exist independently of their
measurementsndash Qualities can have zero or more measurements
These are not the names of qualitiesndash percentagendash processndash abnormalndash high
44
Some examples of qualities
The particular redness of the left eye of a single individual flyndash An instance of a quality type
The color lsquoredrsquondash A quality type
Note the eye does not instantiate lsquoredrsquo
PATO represents quality types (universals)ndash PATO definitions can be used to classify quality
instances by the types they instantiate
45
the particular case ofredness (of a particularfly eye)
the type ldquoredrdquo
instantiates
an instance of an eye(in a particular fly)
the type ldquoeyerdquo
instantiates
inheresin (is aquality ofhas_bearer)
46
Qualities are dependent entities
Qualities require bearersndash Bearers can be physical objects or processes
Examplendash A shape requires a physical object to bear itndash If the physical object ceases to exist (eg it
decomposes) then the shape ceases to exist
48
Scale Bearer Quality Definition (proposed)
Physical Continuant Mass Equivalent to the sum of the mass of the parts of the bearer (mass at the particle level is primitiveoutwith PATO)
Physical Continuant Opacity An optical quality manifest by the capacity of the bearer to block light
PhysChem Liquid Concentration A compositional relational quality manifest by the relative quantity of some chemical type contained by the bearer
Molecular Gene splicing quality manifest by the splicing processes undergone by the bearer
Cellular Cell ploidy A cellular quality manifest by the number of genomes that are part of the bearer
Cellular Cell transformative potency
A cellular quality manifest by the capacity of the bearer cell to differentiate to different cell types
Organismal Tissue tone
Organismal Organism reproductive quality
49
How many types of shape are there
notched T-shaped Y-shaped branched unbranched antrose retrose curled curved wiggly squiggly round flat square oblong elliptical ovoid cuboid spherical egg-shaped rod-shaped heart-shaped hellip
How do we define them
How do we compare them
Shapes cannot be organized in a linear scale
Compare problem of classifying RNA structures
50
Standard case monadic qualitiesExamples
ndash E=kidney Q=hypertrophiedndash autodef a kidney which is hypertrophied
We assume that there is more contextual data (not shown)ndash eg genotype environment number of organisms
in study that showed phenotype
Interpretation (with the rest of the database record)ndash all fish in this experiment with a particular
genotype had a hypertrophied kidney at some point in time
51
Who should use PATO
Originallyndash model organism mutant phenotypes
But alsondash ontology-based evolutionary systematicsndash neuroscience BIRNndash clinical uses
bull OMIMbull clinical records (clinical manifestations)bull drug effects chemical effects
ndash to define terms in other ontologiesbull eg diploid cell invasive tumor engineered gene
condensed chromosome
- The Ontology of Experiments + PATO
- Plan
- EXPO
- Slide 4
- EXPO Formalisation of Science
- Slide 6
- Slide 7
- Slide 8
- Suggested Upper Merged Ontology
- SUMO top level
- Suggested Upper Merged Ontology
- SUMO Structure
- SUMO+Domain Ontology
- Slide 14
- Slide 15
- advantages of SUMO
- problems with SUMO as Upper-Level
- Slide 18
- Slide 19
- Slide 20
- Slide 21
- OBI
- Overview of the Ontology of Biomedical Investigations
- OBI neacutee FuGO
- Motivation for OBI
- Emerging FuGO Design Principles
- OBI Collaborating Communities
- Slide 28
- Slide 29
- FuGO - Top Level Universals
- Slide 31
- Slide 32
- Basic Formal Ontology
- Three dichotomies
- instance vs type
- BFO
- Slide 37
- Slide 38
- Unifying goal integration
- Some thoughts on the ontology itself
- Itrsquos all about the definitions
- Old PATO Entity ndash Attribute ndash Value Eye ndash Red ndash Dark
- What a quality is NOT
- Some examples of qualities
- Slide 45
- Qualities are dependent entities
- Slide 48
- How many types of shape are there
- Standard case monadic qualities
- Who should use PATO
-
28
29
30
FuGO - Top Level Universals Continuant an entity that endureremains the same through time
bull Dependent Continuant depend on another entityEg Environment (depend on the set of ranges of conditions eg geographic location)
Eg Characteristics (entity that can be measured eg temperature unit)
- Realizable an entity that is realizable through a process (executedrun)Eg Software (a set of machine instructions)
Eg Design (the plan that can be realized in a process)
Eg Role (the part played by an entity within the context of a process)
bull Independent Continuant stands on its ownEg All physical entity (instrument technology platform document etc)
Eg Biological material (organism population etc)
Occurrent an entity that occursunfold in timebull Eg Temporal Regions Spatio-Temporal Regions (single actions or Event)
bull Process Eg Investigation (the entire lsquoexperimentalrsquo process)Eg Study (process of acquiring and treating the biological material)Eg Assay (process of performing some tests and recording the results)
31
32
33
Basic Formal Ontologya true upper level ontologyno interference with domain ontologiesno interference with physics cognitionno abstractano negative entitiesexplicit treatment of instances types and relations
34
Three dichotomies
instance vs type
continuant vs occurrent
dependent vs independent
everything in the ontology is a type
types exist in reality through their instances
35
instance vs type
experiments as instances
experiments as types
ontologies relate to types (kinds universals)
we need to keep track of instances in databases
36
BFO
ContinuantOccurrent(Process)
IndependentContinuant
DependentContinuant
37
BFO
ContinuantOccurrent(Process)
IndependentContinuant
(molecule cell organorganism)
DependentContinuant
(quality functiondisease)
Functioning Side-Effect Stochastic Process
38
BFO
ContinuantOccurrent(Process)
IndependentContinuant
(molecule cell organorganism)
PATO Functioning Side-Effect Stochastic Process
39
Unifying goal integration
Integrating datandash within and across these domainsndash across levels of granularityndash across different perspectives
Requiresndash Rigorous formal definitions in both ontologies
and annotation schemas
40
Some thoughts on the ontology itself
Outlinendash Definitions
bull how do we define PATO termsbull what exactly is it wersquore defining
ndash is_a hierarchybull what are the top-level distinctionsbull what are the finer grained distinctions
ndash shapes and colors
41
Itrsquos all about the definitions
OBO Foundry Principlendash Definitions should describe things in reality
not how terms are usedbull definitions should not use the word lsquodescribingrsquo
Scope of PATO = Phenotypic qualities
42
Old PATOEntity ndash Attribute ndash Value
Eye ndash Red ndash Dark
New PATOEntity ndash Quality
Eye ndash Red Eye ndash Dark Red
Dark Red is_a Red
43
What a quality is NOT
Qualities are not measurementsndash Instances of qualities exist independently of their
measurementsndash Qualities can have zero or more measurements
These are not the names of qualitiesndash percentagendash processndash abnormalndash high
44
Some examples of qualities
The particular redness of the left eye of a single individual flyndash An instance of a quality type
The color lsquoredrsquondash A quality type
Note the eye does not instantiate lsquoredrsquo
PATO represents quality types (universals)ndash PATO definitions can be used to classify quality
instances by the types they instantiate
45
the particular case ofredness (of a particularfly eye)
the type ldquoredrdquo
instantiates
an instance of an eye(in a particular fly)
the type ldquoeyerdquo
instantiates
inheresin (is aquality ofhas_bearer)
46
Qualities are dependent entities
Qualities require bearersndash Bearers can be physical objects or processes
Examplendash A shape requires a physical object to bear itndash If the physical object ceases to exist (eg it
decomposes) then the shape ceases to exist
48
Scale Bearer Quality Definition (proposed)
Physical Continuant Mass Equivalent to the sum of the mass of the parts of the bearer (mass at the particle level is primitiveoutwith PATO)
Physical Continuant Opacity An optical quality manifest by the capacity of the bearer to block light
PhysChem Liquid Concentration A compositional relational quality manifest by the relative quantity of some chemical type contained by the bearer
Molecular Gene splicing quality manifest by the splicing processes undergone by the bearer
Cellular Cell ploidy A cellular quality manifest by the number of genomes that are part of the bearer
Cellular Cell transformative potency
A cellular quality manifest by the capacity of the bearer cell to differentiate to different cell types
Organismal Tissue tone
Organismal Organism reproductive quality
49
How many types of shape are there
notched T-shaped Y-shaped branched unbranched antrose retrose curled curved wiggly squiggly round flat square oblong elliptical ovoid cuboid spherical egg-shaped rod-shaped heart-shaped hellip
How do we define them
How do we compare them
Shapes cannot be organized in a linear scale
Compare problem of classifying RNA structures
50
Standard case monadic qualitiesExamples
ndash E=kidney Q=hypertrophiedndash autodef a kidney which is hypertrophied
We assume that there is more contextual data (not shown)ndash eg genotype environment number of organisms
in study that showed phenotype
Interpretation (with the rest of the database record)ndash all fish in this experiment with a particular
genotype had a hypertrophied kidney at some point in time
51
Who should use PATO
Originallyndash model organism mutant phenotypes
But alsondash ontology-based evolutionary systematicsndash neuroscience BIRNndash clinical uses
bull OMIMbull clinical records (clinical manifestations)bull drug effects chemical effects
ndash to define terms in other ontologiesbull eg diploid cell invasive tumor engineered gene
condensed chromosome
- The Ontology of Experiments + PATO
- Plan
- EXPO
- Slide 4
- EXPO Formalisation of Science
- Slide 6
- Slide 7
- Slide 8
- Suggested Upper Merged Ontology
- SUMO top level
- Suggested Upper Merged Ontology
- SUMO Structure
- SUMO+Domain Ontology
- Slide 14
- Slide 15
- advantages of SUMO
- problems with SUMO as Upper-Level
- Slide 18
- Slide 19
- Slide 20
- Slide 21
- OBI
- Overview of the Ontology of Biomedical Investigations
- OBI neacutee FuGO
- Motivation for OBI
- Emerging FuGO Design Principles
- OBI Collaborating Communities
- Slide 28
- Slide 29
- FuGO - Top Level Universals
- Slide 31
- Slide 32
- Basic Formal Ontology
- Three dichotomies
- instance vs type
- BFO
- Slide 37
- Slide 38
- Unifying goal integration
- Some thoughts on the ontology itself
- Itrsquos all about the definitions
- Old PATO Entity ndash Attribute ndash Value Eye ndash Red ndash Dark
- What a quality is NOT
- Some examples of qualities
- Slide 45
- Qualities are dependent entities
- Slide 48
- How many types of shape are there
- Standard case monadic qualities
- Who should use PATO
-
29
30
FuGO - Top Level Universals Continuant an entity that endureremains the same through time
bull Dependent Continuant depend on another entityEg Environment (depend on the set of ranges of conditions eg geographic location)
Eg Characteristics (entity that can be measured eg temperature unit)
- Realizable an entity that is realizable through a process (executedrun)Eg Software (a set of machine instructions)
Eg Design (the plan that can be realized in a process)
Eg Role (the part played by an entity within the context of a process)
bull Independent Continuant stands on its ownEg All physical entity (instrument technology platform document etc)
Eg Biological material (organism population etc)
Occurrent an entity that occursunfold in timebull Eg Temporal Regions Spatio-Temporal Regions (single actions or Event)
bull Process Eg Investigation (the entire lsquoexperimentalrsquo process)Eg Study (process of acquiring and treating the biological material)Eg Assay (process of performing some tests and recording the results)
31
32
33
Basic Formal Ontologya true upper level ontologyno interference with domain ontologiesno interference with physics cognitionno abstractano negative entitiesexplicit treatment of instances types and relations
34
Three dichotomies
instance vs type
continuant vs occurrent
dependent vs independent
everything in the ontology is a type
types exist in reality through their instances
35
instance vs type
experiments as instances
experiments as types
ontologies relate to types (kinds universals)
we need to keep track of instances in databases
36
BFO
ContinuantOccurrent(Process)
IndependentContinuant
DependentContinuant
37
BFO
ContinuantOccurrent(Process)
IndependentContinuant
(molecule cell organorganism)
DependentContinuant
(quality functiondisease)
Functioning Side-Effect Stochastic Process
38
BFO
ContinuantOccurrent(Process)
IndependentContinuant
(molecule cell organorganism)
PATO Functioning Side-Effect Stochastic Process
39
Unifying goal integration
Integrating datandash within and across these domainsndash across levels of granularityndash across different perspectives
Requiresndash Rigorous formal definitions in both ontologies
and annotation schemas
40
Some thoughts on the ontology itself
Outlinendash Definitions
bull how do we define PATO termsbull what exactly is it wersquore defining
ndash is_a hierarchybull what are the top-level distinctionsbull what are the finer grained distinctions
ndash shapes and colors
41
Itrsquos all about the definitions
OBO Foundry Principlendash Definitions should describe things in reality
not how terms are usedbull definitions should not use the word lsquodescribingrsquo
Scope of PATO = Phenotypic qualities
42
Old PATOEntity ndash Attribute ndash Value
Eye ndash Red ndash Dark
New PATOEntity ndash Quality
Eye ndash Red Eye ndash Dark Red
Dark Red is_a Red
43
What a quality is NOT
Qualities are not measurementsndash Instances of qualities exist independently of their
measurementsndash Qualities can have zero or more measurements
These are not the names of qualitiesndash percentagendash processndash abnormalndash high
44
Some examples of qualities
The particular redness of the left eye of a single individual flyndash An instance of a quality type
The color lsquoredrsquondash A quality type
Note the eye does not instantiate lsquoredrsquo
PATO represents quality types (universals)ndash PATO definitions can be used to classify quality
instances by the types they instantiate
45
the particular case ofredness (of a particularfly eye)
the type ldquoredrdquo
instantiates
an instance of an eye(in a particular fly)
the type ldquoeyerdquo
instantiates
inheresin (is aquality ofhas_bearer)
46
Qualities are dependent entities
Qualities require bearersndash Bearers can be physical objects or processes
Examplendash A shape requires a physical object to bear itndash If the physical object ceases to exist (eg it
decomposes) then the shape ceases to exist
48
Scale Bearer Quality Definition (proposed)
Physical Continuant Mass Equivalent to the sum of the mass of the parts of the bearer (mass at the particle level is primitiveoutwith PATO)
Physical Continuant Opacity An optical quality manifest by the capacity of the bearer to block light
PhysChem Liquid Concentration A compositional relational quality manifest by the relative quantity of some chemical type contained by the bearer
Molecular Gene splicing quality manifest by the splicing processes undergone by the bearer
Cellular Cell ploidy A cellular quality manifest by the number of genomes that are part of the bearer
Cellular Cell transformative potency
A cellular quality manifest by the capacity of the bearer cell to differentiate to different cell types
Organismal Tissue tone
Organismal Organism reproductive quality
49
How many types of shape are there
notched T-shaped Y-shaped branched unbranched antrose retrose curled curved wiggly squiggly round flat square oblong elliptical ovoid cuboid spherical egg-shaped rod-shaped heart-shaped hellip
How do we define them
How do we compare them
Shapes cannot be organized in a linear scale
Compare problem of classifying RNA structures
50
Standard case monadic qualitiesExamples
ndash E=kidney Q=hypertrophiedndash autodef a kidney which is hypertrophied
We assume that there is more contextual data (not shown)ndash eg genotype environment number of organisms
in study that showed phenotype
Interpretation (with the rest of the database record)ndash all fish in this experiment with a particular
genotype had a hypertrophied kidney at some point in time
51
Who should use PATO
Originallyndash model organism mutant phenotypes
But alsondash ontology-based evolutionary systematicsndash neuroscience BIRNndash clinical uses
bull OMIMbull clinical records (clinical manifestations)bull drug effects chemical effects
ndash to define terms in other ontologiesbull eg diploid cell invasive tumor engineered gene
condensed chromosome
- The Ontology of Experiments + PATO
- Plan
- EXPO
- Slide 4
- EXPO Formalisation of Science
- Slide 6
- Slide 7
- Slide 8
- Suggested Upper Merged Ontology
- SUMO top level
- Suggested Upper Merged Ontology
- SUMO Structure
- SUMO+Domain Ontology
- Slide 14
- Slide 15
- advantages of SUMO
- problems with SUMO as Upper-Level
- Slide 18
- Slide 19
- Slide 20
- Slide 21
- OBI
- Overview of the Ontology of Biomedical Investigations
- OBI neacutee FuGO
- Motivation for OBI
- Emerging FuGO Design Principles
- OBI Collaborating Communities
- Slide 28
- Slide 29
- FuGO - Top Level Universals
- Slide 31
- Slide 32
- Basic Formal Ontology
- Three dichotomies
- instance vs type
- BFO
- Slide 37
- Slide 38
- Unifying goal integration
- Some thoughts on the ontology itself
- Itrsquos all about the definitions
- Old PATO Entity ndash Attribute ndash Value Eye ndash Red ndash Dark
- What a quality is NOT
- Some examples of qualities
- Slide 45
- Qualities are dependent entities
- Slide 48
- How many types of shape are there
- Standard case monadic qualities
- Who should use PATO
-
30
FuGO - Top Level Universals Continuant an entity that endureremains the same through time
bull Dependent Continuant depend on another entityEg Environment (depend on the set of ranges of conditions eg geographic location)
Eg Characteristics (entity that can be measured eg temperature unit)
- Realizable an entity that is realizable through a process (executedrun)Eg Software (a set of machine instructions)
Eg Design (the plan that can be realized in a process)
Eg Role (the part played by an entity within the context of a process)
bull Independent Continuant stands on its ownEg All physical entity (instrument technology platform document etc)
Eg Biological material (organism population etc)
Occurrent an entity that occursunfold in timebull Eg Temporal Regions Spatio-Temporal Regions (single actions or Event)
bull Process Eg Investigation (the entire lsquoexperimentalrsquo process)Eg Study (process of acquiring and treating the biological material)Eg Assay (process of performing some tests and recording the results)
31
32
33
Basic Formal Ontologya true upper level ontologyno interference with domain ontologiesno interference with physics cognitionno abstractano negative entitiesexplicit treatment of instances types and relations
34
Three dichotomies
instance vs type
continuant vs occurrent
dependent vs independent
everything in the ontology is a type
types exist in reality through their instances
35
instance vs type
experiments as instances
experiments as types
ontologies relate to types (kinds universals)
we need to keep track of instances in databases
36
BFO
ContinuantOccurrent(Process)
IndependentContinuant
DependentContinuant
37
BFO
ContinuantOccurrent(Process)
IndependentContinuant
(molecule cell organorganism)
DependentContinuant
(quality functiondisease)
Functioning Side-Effect Stochastic Process
38
BFO
ContinuantOccurrent(Process)
IndependentContinuant
(molecule cell organorganism)
PATO Functioning Side-Effect Stochastic Process
39
Unifying goal integration
Integrating datandash within and across these domainsndash across levels of granularityndash across different perspectives
Requiresndash Rigorous formal definitions in both ontologies
and annotation schemas
40
Some thoughts on the ontology itself
Outlinendash Definitions
bull how do we define PATO termsbull what exactly is it wersquore defining
ndash is_a hierarchybull what are the top-level distinctionsbull what are the finer grained distinctions
ndash shapes and colors
41
Itrsquos all about the definitions
OBO Foundry Principlendash Definitions should describe things in reality
not how terms are usedbull definitions should not use the word lsquodescribingrsquo
Scope of PATO = Phenotypic qualities
42
Old PATOEntity ndash Attribute ndash Value
Eye ndash Red ndash Dark
New PATOEntity ndash Quality
Eye ndash Red Eye ndash Dark Red
Dark Red is_a Red
43
What a quality is NOT
Qualities are not measurementsndash Instances of qualities exist independently of their
measurementsndash Qualities can have zero or more measurements
These are not the names of qualitiesndash percentagendash processndash abnormalndash high
44
Some examples of qualities
The particular redness of the left eye of a single individual flyndash An instance of a quality type
The color lsquoredrsquondash A quality type
Note the eye does not instantiate lsquoredrsquo
PATO represents quality types (universals)ndash PATO definitions can be used to classify quality
instances by the types they instantiate
45
the particular case ofredness (of a particularfly eye)
the type ldquoredrdquo
instantiates
an instance of an eye(in a particular fly)
the type ldquoeyerdquo
instantiates
inheresin (is aquality ofhas_bearer)
46
Qualities are dependent entities
Qualities require bearersndash Bearers can be physical objects or processes
Examplendash A shape requires a physical object to bear itndash If the physical object ceases to exist (eg it
decomposes) then the shape ceases to exist
48
Scale Bearer Quality Definition (proposed)
Physical Continuant Mass Equivalent to the sum of the mass of the parts of the bearer (mass at the particle level is primitiveoutwith PATO)
Physical Continuant Opacity An optical quality manifest by the capacity of the bearer to block light
PhysChem Liquid Concentration A compositional relational quality manifest by the relative quantity of some chemical type contained by the bearer
Molecular Gene splicing quality manifest by the splicing processes undergone by the bearer
Cellular Cell ploidy A cellular quality manifest by the number of genomes that are part of the bearer
Cellular Cell transformative potency
A cellular quality manifest by the capacity of the bearer cell to differentiate to different cell types
Organismal Tissue tone
Organismal Organism reproductive quality
49
How many types of shape are there
notched T-shaped Y-shaped branched unbranched antrose retrose curled curved wiggly squiggly round flat square oblong elliptical ovoid cuboid spherical egg-shaped rod-shaped heart-shaped hellip
How do we define them
How do we compare them
Shapes cannot be organized in a linear scale
Compare problem of classifying RNA structures
50
Standard case monadic qualitiesExamples
ndash E=kidney Q=hypertrophiedndash autodef a kidney which is hypertrophied
We assume that there is more contextual data (not shown)ndash eg genotype environment number of organisms
in study that showed phenotype
Interpretation (with the rest of the database record)ndash all fish in this experiment with a particular
genotype had a hypertrophied kidney at some point in time
51
Who should use PATO
Originallyndash model organism mutant phenotypes
But alsondash ontology-based evolutionary systematicsndash neuroscience BIRNndash clinical uses
bull OMIMbull clinical records (clinical manifestations)bull drug effects chemical effects
ndash to define terms in other ontologiesbull eg diploid cell invasive tumor engineered gene
condensed chromosome
- The Ontology of Experiments + PATO
- Plan
- EXPO
- Slide 4
- EXPO Formalisation of Science
- Slide 6
- Slide 7
- Slide 8
- Suggested Upper Merged Ontology
- SUMO top level
- Suggested Upper Merged Ontology
- SUMO Structure
- SUMO+Domain Ontology
- Slide 14
- Slide 15
- advantages of SUMO
- problems with SUMO as Upper-Level
- Slide 18
- Slide 19
- Slide 20
- Slide 21
- OBI
- Overview of the Ontology of Biomedical Investigations
- OBI neacutee FuGO
- Motivation for OBI
- Emerging FuGO Design Principles
- OBI Collaborating Communities
- Slide 28
- Slide 29
- FuGO - Top Level Universals
- Slide 31
- Slide 32
- Basic Formal Ontology
- Three dichotomies
- instance vs type
- BFO
- Slide 37
- Slide 38
- Unifying goal integration
- Some thoughts on the ontology itself
- Itrsquos all about the definitions
- Old PATO Entity ndash Attribute ndash Value Eye ndash Red ndash Dark
- What a quality is NOT
- Some examples of qualities
- Slide 45
- Qualities are dependent entities
- Slide 48
- How many types of shape are there
- Standard case monadic qualities
- Who should use PATO
-
31
32
33
Basic Formal Ontologya true upper level ontologyno interference with domain ontologiesno interference with physics cognitionno abstractano negative entitiesexplicit treatment of instances types and relations
34
Three dichotomies
instance vs type
continuant vs occurrent
dependent vs independent
everything in the ontology is a type
types exist in reality through their instances
35
instance vs type
experiments as instances
experiments as types
ontologies relate to types (kinds universals)
we need to keep track of instances in databases
36
BFO
ContinuantOccurrent(Process)
IndependentContinuant
DependentContinuant
37
BFO
ContinuantOccurrent(Process)
IndependentContinuant
(molecule cell organorganism)
DependentContinuant
(quality functiondisease)
Functioning Side-Effect Stochastic Process
38
BFO
ContinuantOccurrent(Process)
IndependentContinuant
(molecule cell organorganism)
PATO Functioning Side-Effect Stochastic Process
39
Unifying goal integration
Integrating datandash within and across these domainsndash across levels of granularityndash across different perspectives
Requiresndash Rigorous formal definitions in both ontologies
and annotation schemas
40
Some thoughts on the ontology itself
Outlinendash Definitions
bull how do we define PATO termsbull what exactly is it wersquore defining
ndash is_a hierarchybull what are the top-level distinctionsbull what are the finer grained distinctions
ndash shapes and colors
41
Itrsquos all about the definitions
OBO Foundry Principlendash Definitions should describe things in reality
not how terms are usedbull definitions should not use the word lsquodescribingrsquo
Scope of PATO = Phenotypic qualities
42
Old PATOEntity ndash Attribute ndash Value
Eye ndash Red ndash Dark
New PATOEntity ndash Quality
Eye ndash Red Eye ndash Dark Red
Dark Red is_a Red
43
What a quality is NOT
Qualities are not measurementsndash Instances of qualities exist independently of their
measurementsndash Qualities can have zero or more measurements
These are not the names of qualitiesndash percentagendash processndash abnormalndash high
44
Some examples of qualities
The particular redness of the left eye of a single individual flyndash An instance of a quality type
The color lsquoredrsquondash A quality type
Note the eye does not instantiate lsquoredrsquo
PATO represents quality types (universals)ndash PATO definitions can be used to classify quality
instances by the types they instantiate
45
the particular case ofredness (of a particularfly eye)
the type ldquoredrdquo
instantiates
an instance of an eye(in a particular fly)
the type ldquoeyerdquo
instantiates
inheresin (is aquality ofhas_bearer)
46
Qualities are dependent entities
Qualities require bearersndash Bearers can be physical objects or processes
Examplendash A shape requires a physical object to bear itndash If the physical object ceases to exist (eg it
decomposes) then the shape ceases to exist
48
Scale Bearer Quality Definition (proposed)
Physical Continuant Mass Equivalent to the sum of the mass of the parts of the bearer (mass at the particle level is primitiveoutwith PATO)
Physical Continuant Opacity An optical quality manifest by the capacity of the bearer to block light
PhysChem Liquid Concentration A compositional relational quality manifest by the relative quantity of some chemical type contained by the bearer
Molecular Gene splicing quality manifest by the splicing processes undergone by the bearer
Cellular Cell ploidy A cellular quality manifest by the number of genomes that are part of the bearer
Cellular Cell transformative potency
A cellular quality manifest by the capacity of the bearer cell to differentiate to different cell types
Organismal Tissue tone
Organismal Organism reproductive quality
49
How many types of shape are there
notched T-shaped Y-shaped branched unbranched antrose retrose curled curved wiggly squiggly round flat square oblong elliptical ovoid cuboid spherical egg-shaped rod-shaped heart-shaped hellip
How do we define them
How do we compare them
Shapes cannot be organized in a linear scale
Compare problem of classifying RNA structures
50
Standard case monadic qualitiesExamples
ndash E=kidney Q=hypertrophiedndash autodef a kidney which is hypertrophied
We assume that there is more contextual data (not shown)ndash eg genotype environment number of organisms
in study that showed phenotype
Interpretation (with the rest of the database record)ndash all fish in this experiment with a particular
genotype had a hypertrophied kidney at some point in time
51
Who should use PATO
Originallyndash model organism mutant phenotypes
But alsondash ontology-based evolutionary systematicsndash neuroscience BIRNndash clinical uses
bull OMIMbull clinical records (clinical manifestations)bull drug effects chemical effects
ndash to define terms in other ontologiesbull eg diploid cell invasive tumor engineered gene
condensed chromosome
- The Ontology of Experiments + PATO
- Plan
- EXPO
- Slide 4
- EXPO Formalisation of Science
- Slide 6
- Slide 7
- Slide 8
- Suggested Upper Merged Ontology
- SUMO top level
- Suggested Upper Merged Ontology
- SUMO Structure
- SUMO+Domain Ontology
- Slide 14
- Slide 15
- advantages of SUMO
- problems with SUMO as Upper-Level
- Slide 18
- Slide 19
- Slide 20
- Slide 21
- OBI
- Overview of the Ontology of Biomedical Investigations
- OBI neacutee FuGO
- Motivation for OBI
- Emerging FuGO Design Principles
- OBI Collaborating Communities
- Slide 28
- Slide 29
- FuGO - Top Level Universals
- Slide 31
- Slide 32
- Basic Formal Ontology
- Three dichotomies
- instance vs type
- BFO
- Slide 37
- Slide 38
- Unifying goal integration
- Some thoughts on the ontology itself
- Itrsquos all about the definitions
- Old PATO Entity ndash Attribute ndash Value Eye ndash Red ndash Dark
- What a quality is NOT
- Some examples of qualities
- Slide 45
- Qualities are dependent entities
- Slide 48
- How many types of shape are there
- Standard case monadic qualities
- Who should use PATO
-
32
33
Basic Formal Ontologya true upper level ontologyno interference with domain ontologiesno interference with physics cognitionno abstractano negative entitiesexplicit treatment of instances types and relations
34
Three dichotomies
instance vs type
continuant vs occurrent
dependent vs independent
everything in the ontology is a type
types exist in reality through their instances
35
instance vs type
experiments as instances
experiments as types
ontologies relate to types (kinds universals)
we need to keep track of instances in databases
36
BFO
ContinuantOccurrent(Process)
IndependentContinuant
DependentContinuant
37
BFO
ContinuantOccurrent(Process)
IndependentContinuant
(molecule cell organorganism)
DependentContinuant
(quality functiondisease)
Functioning Side-Effect Stochastic Process
38
BFO
ContinuantOccurrent(Process)
IndependentContinuant
(molecule cell organorganism)
PATO Functioning Side-Effect Stochastic Process
39
Unifying goal integration
Integrating datandash within and across these domainsndash across levels of granularityndash across different perspectives
Requiresndash Rigorous formal definitions in both ontologies
and annotation schemas
40
Some thoughts on the ontology itself
Outlinendash Definitions
bull how do we define PATO termsbull what exactly is it wersquore defining
ndash is_a hierarchybull what are the top-level distinctionsbull what are the finer grained distinctions
ndash shapes and colors
41
Itrsquos all about the definitions
OBO Foundry Principlendash Definitions should describe things in reality
not how terms are usedbull definitions should not use the word lsquodescribingrsquo
Scope of PATO = Phenotypic qualities
42
Old PATOEntity ndash Attribute ndash Value
Eye ndash Red ndash Dark
New PATOEntity ndash Quality
Eye ndash Red Eye ndash Dark Red
Dark Red is_a Red
43
What a quality is NOT
Qualities are not measurementsndash Instances of qualities exist independently of their
measurementsndash Qualities can have zero or more measurements
These are not the names of qualitiesndash percentagendash processndash abnormalndash high
44
Some examples of qualities
The particular redness of the left eye of a single individual flyndash An instance of a quality type
The color lsquoredrsquondash A quality type
Note the eye does not instantiate lsquoredrsquo
PATO represents quality types (universals)ndash PATO definitions can be used to classify quality
instances by the types they instantiate
45
the particular case ofredness (of a particularfly eye)
the type ldquoredrdquo
instantiates
an instance of an eye(in a particular fly)
the type ldquoeyerdquo
instantiates
inheresin (is aquality ofhas_bearer)
46
Qualities are dependent entities
Qualities require bearersndash Bearers can be physical objects or processes
Examplendash A shape requires a physical object to bear itndash If the physical object ceases to exist (eg it
decomposes) then the shape ceases to exist
48
Scale Bearer Quality Definition (proposed)
Physical Continuant Mass Equivalent to the sum of the mass of the parts of the bearer (mass at the particle level is primitiveoutwith PATO)
Physical Continuant Opacity An optical quality manifest by the capacity of the bearer to block light
PhysChem Liquid Concentration A compositional relational quality manifest by the relative quantity of some chemical type contained by the bearer
Molecular Gene splicing quality manifest by the splicing processes undergone by the bearer
Cellular Cell ploidy A cellular quality manifest by the number of genomes that are part of the bearer
Cellular Cell transformative potency
A cellular quality manifest by the capacity of the bearer cell to differentiate to different cell types
Organismal Tissue tone
Organismal Organism reproductive quality
49
How many types of shape are there
notched T-shaped Y-shaped branched unbranched antrose retrose curled curved wiggly squiggly round flat square oblong elliptical ovoid cuboid spherical egg-shaped rod-shaped heart-shaped hellip
How do we define them
How do we compare them
Shapes cannot be organized in a linear scale
Compare problem of classifying RNA structures
50
Standard case monadic qualitiesExamples
ndash E=kidney Q=hypertrophiedndash autodef a kidney which is hypertrophied
We assume that there is more contextual data (not shown)ndash eg genotype environment number of organisms
in study that showed phenotype
Interpretation (with the rest of the database record)ndash all fish in this experiment with a particular
genotype had a hypertrophied kidney at some point in time
51
Who should use PATO
Originallyndash model organism mutant phenotypes
But alsondash ontology-based evolutionary systematicsndash neuroscience BIRNndash clinical uses
bull OMIMbull clinical records (clinical manifestations)bull drug effects chemical effects
ndash to define terms in other ontologiesbull eg diploid cell invasive tumor engineered gene
condensed chromosome
- The Ontology of Experiments + PATO
- Plan
- EXPO
- Slide 4
- EXPO Formalisation of Science
- Slide 6
- Slide 7
- Slide 8
- Suggested Upper Merged Ontology
- SUMO top level
- Suggested Upper Merged Ontology
- SUMO Structure
- SUMO+Domain Ontology
- Slide 14
- Slide 15
- advantages of SUMO
- problems with SUMO as Upper-Level
- Slide 18
- Slide 19
- Slide 20
- Slide 21
- OBI
- Overview of the Ontology of Biomedical Investigations
- OBI neacutee FuGO
- Motivation for OBI
- Emerging FuGO Design Principles
- OBI Collaborating Communities
- Slide 28
- Slide 29
- FuGO - Top Level Universals
- Slide 31
- Slide 32
- Basic Formal Ontology
- Three dichotomies
- instance vs type
- BFO
- Slide 37
- Slide 38
- Unifying goal integration
- Some thoughts on the ontology itself
- Itrsquos all about the definitions
- Old PATO Entity ndash Attribute ndash Value Eye ndash Red ndash Dark
- What a quality is NOT
- Some examples of qualities
- Slide 45
- Qualities are dependent entities
- Slide 48
- How many types of shape are there
- Standard case monadic qualities
- Who should use PATO
-
33
Basic Formal Ontologya true upper level ontologyno interference with domain ontologiesno interference with physics cognitionno abstractano negative entitiesexplicit treatment of instances types and relations
34
Three dichotomies
instance vs type
continuant vs occurrent
dependent vs independent
everything in the ontology is a type
types exist in reality through their instances
35
instance vs type
experiments as instances
experiments as types
ontologies relate to types (kinds universals)
we need to keep track of instances in databases
36
BFO
ContinuantOccurrent(Process)
IndependentContinuant
DependentContinuant
37
BFO
ContinuantOccurrent(Process)
IndependentContinuant
(molecule cell organorganism)
DependentContinuant
(quality functiondisease)
Functioning Side-Effect Stochastic Process
38
BFO
ContinuantOccurrent(Process)
IndependentContinuant
(molecule cell organorganism)
PATO Functioning Side-Effect Stochastic Process
39
Unifying goal integration
Integrating datandash within and across these domainsndash across levels of granularityndash across different perspectives
Requiresndash Rigorous formal definitions in both ontologies
and annotation schemas
40
Some thoughts on the ontology itself
Outlinendash Definitions
bull how do we define PATO termsbull what exactly is it wersquore defining
ndash is_a hierarchybull what are the top-level distinctionsbull what are the finer grained distinctions
ndash shapes and colors
41
Itrsquos all about the definitions
OBO Foundry Principlendash Definitions should describe things in reality
not how terms are usedbull definitions should not use the word lsquodescribingrsquo
Scope of PATO = Phenotypic qualities
42
Old PATOEntity ndash Attribute ndash Value
Eye ndash Red ndash Dark
New PATOEntity ndash Quality
Eye ndash Red Eye ndash Dark Red
Dark Red is_a Red
43
What a quality is NOT
Qualities are not measurementsndash Instances of qualities exist independently of their
measurementsndash Qualities can have zero or more measurements
These are not the names of qualitiesndash percentagendash processndash abnormalndash high
44
Some examples of qualities
The particular redness of the left eye of a single individual flyndash An instance of a quality type
The color lsquoredrsquondash A quality type
Note the eye does not instantiate lsquoredrsquo
PATO represents quality types (universals)ndash PATO definitions can be used to classify quality
instances by the types they instantiate
45
the particular case ofredness (of a particularfly eye)
the type ldquoredrdquo
instantiates
an instance of an eye(in a particular fly)
the type ldquoeyerdquo
instantiates
inheresin (is aquality ofhas_bearer)
46
Qualities are dependent entities
Qualities require bearersndash Bearers can be physical objects or processes
Examplendash A shape requires a physical object to bear itndash If the physical object ceases to exist (eg it
decomposes) then the shape ceases to exist
48
Scale Bearer Quality Definition (proposed)
Physical Continuant Mass Equivalent to the sum of the mass of the parts of the bearer (mass at the particle level is primitiveoutwith PATO)
Physical Continuant Opacity An optical quality manifest by the capacity of the bearer to block light
PhysChem Liquid Concentration A compositional relational quality manifest by the relative quantity of some chemical type contained by the bearer
Molecular Gene splicing quality manifest by the splicing processes undergone by the bearer
Cellular Cell ploidy A cellular quality manifest by the number of genomes that are part of the bearer
Cellular Cell transformative potency
A cellular quality manifest by the capacity of the bearer cell to differentiate to different cell types
Organismal Tissue tone
Organismal Organism reproductive quality
49
How many types of shape are there
notched T-shaped Y-shaped branched unbranched antrose retrose curled curved wiggly squiggly round flat square oblong elliptical ovoid cuboid spherical egg-shaped rod-shaped heart-shaped hellip
How do we define them
How do we compare them
Shapes cannot be organized in a linear scale
Compare problem of classifying RNA structures
50
Standard case monadic qualitiesExamples
ndash E=kidney Q=hypertrophiedndash autodef a kidney which is hypertrophied
We assume that there is more contextual data (not shown)ndash eg genotype environment number of organisms
in study that showed phenotype
Interpretation (with the rest of the database record)ndash all fish in this experiment with a particular
genotype had a hypertrophied kidney at some point in time
51
Who should use PATO
Originallyndash model organism mutant phenotypes
But alsondash ontology-based evolutionary systematicsndash neuroscience BIRNndash clinical uses
bull OMIMbull clinical records (clinical manifestations)bull drug effects chemical effects
ndash to define terms in other ontologiesbull eg diploid cell invasive tumor engineered gene
condensed chromosome
- The Ontology of Experiments + PATO
- Plan
- EXPO
- Slide 4
- EXPO Formalisation of Science
- Slide 6
- Slide 7
- Slide 8
- Suggested Upper Merged Ontology
- SUMO top level
- Suggested Upper Merged Ontology
- SUMO Structure
- SUMO+Domain Ontology
- Slide 14
- Slide 15
- advantages of SUMO
- problems with SUMO as Upper-Level
- Slide 18
- Slide 19
- Slide 20
- Slide 21
- OBI
- Overview of the Ontology of Biomedical Investigations
- OBI neacutee FuGO
- Motivation for OBI
- Emerging FuGO Design Principles
- OBI Collaborating Communities
- Slide 28
- Slide 29
- FuGO - Top Level Universals
- Slide 31
- Slide 32
- Basic Formal Ontology
- Three dichotomies
- instance vs type
- BFO
- Slide 37
- Slide 38
- Unifying goal integration
- Some thoughts on the ontology itself
- Itrsquos all about the definitions
- Old PATO Entity ndash Attribute ndash Value Eye ndash Red ndash Dark
- What a quality is NOT
- Some examples of qualities
- Slide 45
- Qualities are dependent entities
- Slide 48
- How many types of shape are there
- Standard case monadic qualities
- Who should use PATO
-
34
Three dichotomies
instance vs type
continuant vs occurrent
dependent vs independent
everything in the ontology is a type
types exist in reality through their instances
35
instance vs type
experiments as instances
experiments as types
ontologies relate to types (kinds universals)
we need to keep track of instances in databases
36
BFO
ContinuantOccurrent(Process)
IndependentContinuant
DependentContinuant
37
BFO
ContinuantOccurrent(Process)
IndependentContinuant
(molecule cell organorganism)
DependentContinuant
(quality functiondisease)
Functioning Side-Effect Stochastic Process
38
BFO
ContinuantOccurrent(Process)
IndependentContinuant
(molecule cell organorganism)
PATO Functioning Side-Effect Stochastic Process
39
Unifying goal integration
Integrating datandash within and across these domainsndash across levels of granularityndash across different perspectives
Requiresndash Rigorous formal definitions in both ontologies
and annotation schemas
40
Some thoughts on the ontology itself
Outlinendash Definitions
bull how do we define PATO termsbull what exactly is it wersquore defining
ndash is_a hierarchybull what are the top-level distinctionsbull what are the finer grained distinctions
ndash shapes and colors
41
Itrsquos all about the definitions
OBO Foundry Principlendash Definitions should describe things in reality
not how terms are usedbull definitions should not use the word lsquodescribingrsquo
Scope of PATO = Phenotypic qualities
42
Old PATOEntity ndash Attribute ndash Value
Eye ndash Red ndash Dark
New PATOEntity ndash Quality
Eye ndash Red Eye ndash Dark Red
Dark Red is_a Red
43
What a quality is NOT
Qualities are not measurementsndash Instances of qualities exist independently of their
measurementsndash Qualities can have zero or more measurements
These are not the names of qualitiesndash percentagendash processndash abnormalndash high
44
Some examples of qualities
The particular redness of the left eye of a single individual flyndash An instance of a quality type
The color lsquoredrsquondash A quality type
Note the eye does not instantiate lsquoredrsquo
PATO represents quality types (universals)ndash PATO definitions can be used to classify quality
instances by the types they instantiate
45
the particular case ofredness (of a particularfly eye)
the type ldquoredrdquo
instantiates
an instance of an eye(in a particular fly)
the type ldquoeyerdquo
instantiates
inheresin (is aquality ofhas_bearer)
46
Qualities are dependent entities
Qualities require bearersndash Bearers can be physical objects or processes
Examplendash A shape requires a physical object to bear itndash If the physical object ceases to exist (eg it
decomposes) then the shape ceases to exist
48
Scale Bearer Quality Definition (proposed)
Physical Continuant Mass Equivalent to the sum of the mass of the parts of the bearer (mass at the particle level is primitiveoutwith PATO)
Physical Continuant Opacity An optical quality manifest by the capacity of the bearer to block light
PhysChem Liquid Concentration A compositional relational quality manifest by the relative quantity of some chemical type contained by the bearer
Molecular Gene splicing quality manifest by the splicing processes undergone by the bearer
Cellular Cell ploidy A cellular quality manifest by the number of genomes that are part of the bearer
Cellular Cell transformative potency
A cellular quality manifest by the capacity of the bearer cell to differentiate to different cell types
Organismal Tissue tone
Organismal Organism reproductive quality
49
How many types of shape are there
notched T-shaped Y-shaped branched unbranched antrose retrose curled curved wiggly squiggly round flat square oblong elliptical ovoid cuboid spherical egg-shaped rod-shaped heart-shaped hellip
How do we define them
How do we compare them
Shapes cannot be organized in a linear scale
Compare problem of classifying RNA structures
50
Standard case monadic qualitiesExamples
ndash E=kidney Q=hypertrophiedndash autodef a kidney which is hypertrophied
We assume that there is more contextual data (not shown)ndash eg genotype environment number of organisms
in study that showed phenotype
Interpretation (with the rest of the database record)ndash all fish in this experiment with a particular
genotype had a hypertrophied kidney at some point in time
51
Who should use PATO
Originallyndash model organism mutant phenotypes
But alsondash ontology-based evolutionary systematicsndash neuroscience BIRNndash clinical uses
bull OMIMbull clinical records (clinical manifestations)bull drug effects chemical effects
ndash to define terms in other ontologiesbull eg diploid cell invasive tumor engineered gene
condensed chromosome
- The Ontology of Experiments + PATO
- Plan
- EXPO
- Slide 4
- EXPO Formalisation of Science
- Slide 6
- Slide 7
- Slide 8
- Suggested Upper Merged Ontology
- SUMO top level
- Suggested Upper Merged Ontology
- SUMO Structure
- SUMO+Domain Ontology
- Slide 14
- Slide 15
- advantages of SUMO
- problems with SUMO as Upper-Level
- Slide 18
- Slide 19
- Slide 20
- Slide 21
- OBI
- Overview of the Ontology of Biomedical Investigations
- OBI neacutee FuGO
- Motivation for OBI
- Emerging FuGO Design Principles
- OBI Collaborating Communities
- Slide 28
- Slide 29
- FuGO - Top Level Universals
- Slide 31
- Slide 32
- Basic Formal Ontology
- Three dichotomies
- instance vs type
- BFO
- Slide 37
- Slide 38
- Unifying goal integration
- Some thoughts on the ontology itself
- Itrsquos all about the definitions
- Old PATO Entity ndash Attribute ndash Value Eye ndash Red ndash Dark
- What a quality is NOT
- Some examples of qualities
- Slide 45
- Qualities are dependent entities
- Slide 48
- How many types of shape are there
- Standard case monadic qualities
- Who should use PATO
-
35
instance vs type
experiments as instances
experiments as types
ontologies relate to types (kinds universals)
we need to keep track of instances in databases
36
BFO
ContinuantOccurrent(Process)
IndependentContinuant
DependentContinuant
37
BFO
ContinuantOccurrent(Process)
IndependentContinuant
(molecule cell organorganism)
DependentContinuant
(quality functiondisease)
Functioning Side-Effect Stochastic Process
38
BFO
ContinuantOccurrent(Process)
IndependentContinuant
(molecule cell organorganism)
PATO Functioning Side-Effect Stochastic Process
39
Unifying goal integration
Integrating datandash within and across these domainsndash across levels of granularityndash across different perspectives
Requiresndash Rigorous formal definitions in both ontologies
and annotation schemas
40
Some thoughts on the ontology itself
Outlinendash Definitions
bull how do we define PATO termsbull what exactly is it wersquore defining
ndash is_a hierarchybull what are the top-level distinctionsbull what are the finer grained distinctions
ndash shapes and colors
41
Itrsquos all about the definitions
OBO Foundry Principlendash Definitions should describe things in reality
not how terms are usedbull definitions should not use the word lsquodescribingrsquo
Scope of PATO = Phenotypic qualities
42
Old PATOEntity ndash Attribute ndash Value
Eye ndash Red ndash Dark
New PATOEntity ndash Quality
Eye ndash Red Eye ndash Dark Red
Dark Red is_a Red
43
What a quality is NOT
Qualities are not measurementsndash Instances of qualities exist independently of their
measurementsndash Qualities can have zero or more measurements
These are not the names of qualitiesndash percentagendash processndash abnormalndash high
44
Some examples of qualities
The particular redness of the left eye of a single individual flyndash An instance of a quality type
The color lsquoredrsquondash A quality type
Note the eye does not instantiate lsquoredrsquo
PATO represents quality types (universals)ndash PATO definitions can be used to classify quality
instances by the types they instantiate
45
the particular case ofredness (of a particularfly eye)
the type ldquoredrdquo
instantiates
an instance of an eye(in a particular fly)
the type ldquoeyerdquo
instantiates
inheresin (is aquality ofhas_bearer)
46
Qualities are dependent entities
Qualities require bearersndash Bearers can be physical objects or processes
Examplendash A shape requires a physical object to bear itndash If the physical object ceases to exist (eg it
decomposes) then the shape ceases to exist
48
Scale Bearer Quality Definition (proposed)
Physical Continuant Mass Equivalent to the sum of the mass of the parts of the bearer (mass at the particle level is primitiveoutwith PATO)
Physical Continuant Opacity An optical quality manifest by the capacity of the bearer to block light
PhysChem Liquid Concentration A compositional relational quality manifest by the relative quantity of some chemical type contained by the bearer
Molecular Gene splicing quality manifest by the splicing processes undergone by the bearer
Cellular Cell ploidy A cellular quality manifest by the number of genomes that are part of the bearer
Cellular Cell transformative potency
A cellular quality manifest by the capacity of the bearer cell to differentiate to different cell types
Organismal Tissue tone
Organismal Organism reproductive quality
49
How many types of shape are there
notched T-shaped Y-shaped branched unbranched antrose retrose curled curved wiggly squiggly round flat square oblong elliptical ovoid cuboid spherical egg-shaped rod-shaped heart-shaped hellip
How do we define them
How do we compare them
Shapes cannot be organized in a linear scale
Compare problem of classifying RNA structures
50
Standard case monadic qualitiesExamples
ndash E=kidney Q=hypertrophiedndash autodef a kidney which is hypertrophied
We assume that there is more contextual data (not shown)ndash eg genotype environment number of organisms
in study that showed phenotype
Interpretation (with the rest of the database record)ndash all fish in this experiment with a particular
genotype had a hypertrophied kidney at some point in time
51
Who should use PATO
Originallyndash model organism mutant phenotypes
But alsondash ontology-based evolutionary systematicsndash neuroscience BIRNndash clinical uses
bull OMIMbull clinical records (clinical manifestations)bull drug effects chemical effects
ndash to define terms in other ontologiesbull eg diploid cell invasive tumor engineered gene
condensed chromosome
- The Ontology of Experiments + PATO
- Plan
- EXPO
- Slide 4
- EXPO Formalisation of Science
- Slide 6
- Slide 7
- Slide 8
- Suggested Upper Merged Ontology
- SUMO top level
- Suggested Upper Merged Ontology
- SUMO Structure
- SUMO+Domain Ontology
- Slide 14
- Slide 15
- advantages of SUMO
- problems with SUMO as Upper-Level
- Slide 18
- Slide 19
- Slide 20
- Slide 21
- OBI
- Overview of the Ontology of Biomedical Investigations
- OBI neacutee FuGO
- Motivation for OBI
- Emerging FuGO Design Principles
- OBI Collaborating Communities
- Slide 28
- Slide 29
- FuGO - Top Level Universals
- Slide 31
- Slide 32
- Basic Formal Ontology
- Three dichotomies
- instance vs type
- BFO
- Slide 37
- Slide 38
- Unifying goal integration
- Some thoughts on the ontology itself
- Itrsquos all about the definitions
- Old PATO Entity ndash Attribute ndash Value Eye ndash Red ndash Dark
- What a quality is NOT
- Some examples of qualities
- Slide 45
- Qualities are dependent entities
- Slide 48
- How many types of shape are there
- Standard case monadic qualities
- Who should use PATO
-
36
BFO
ContinuantOccurrent(Process)
IndependentContinuant
DependentContinuant
37
BFO
ContinuantOccurrent(Process)
IndependentContinuant
(molecule cell organorganism)
DependentContinuant
(quality functiondisease)
Functioning Side-Effect Stochastic Process
38
BFO
ContinuantOccurrent(Process)
IndependentContinuant
(molecule cell organorganism)
PATO Functioning Side-Effect Stochastic Process
39
Unifying goal integration
Integrating datandash within and across these domainsndash across levels of granularityndash across different perspectives
Requiresndash Rigorous formal definitions in both ontologies
and annotation schemas
40
Some thoughts on the ontology itself
Outlinendash Definitions
bull how do we define PATO termsbull what exactly is it wersquore defining
ndash is_a hierarchybull what are the top-level distinctionsbull what are the finer grained distinctions
ndash shapes and colors
41
Itrsquos all about the definitions
OBO Foundry Principlendash Definitions should describe things in reality
not how terms are usedbull definitions should not use the word lsquodescribingrsquo
Scope of PATO = Phenotypic qualities
42
Old PATOEntity ndash Attribute ndash Value
Eye ndash Red ndash Dark
New PATOEntity ndash Quality
Eye ndash Red Eye ndash Dark Red
Dark Red is_a Red
43
What a quality is NOT
Qualities are not measurementsndash Instances of qualities exist independently of their
measurementsndash Qualities can have zero or more measurements
These are not the names of qualitiesndash percentagendash processndash abnormalndash high
44
Some examples of qualities
The particular redness of the left eye of a single individual flyndash An instance of a quality type
The color lsquoredrsquondash A quality type
Note the eye does not instantiate lsquoredrsquo
PATO represents quality types (universals)ndash PATO definitions can be used to classify quality
instances by the types they instantiate
45
the particular case ofredness (of a particularfly eye)
the type ldquoredrdquo
instantiates
an instance of an eye(in a particular fly)
the type ldquoeyerdquo
instantiates
inheresin (is aquality ofhas_bearer)
46
Qualities are dependent entities
Qualities require bearersndash Bearers can be physical objects or processes
Examplendash A shape requires a physical object to bear itndash If the physical object ceases to exist (eg it
decomposes) then the shape ceases to exist
48
Scale Bearer Quality Definition (proposed)
Physical Continuant Mass Equivalent to the sum of the mass of the parts of the bearer (mass at the particle level is primitiveoutwith PATO)
Physical Continuant Opacity An optical quality manifest by the capacity of the bearer to block light
PhysChem Liquid Concentration A compositional relational quality manifest by the relative quantity of some chemical type contained by the bearer
Molecular Gene splicing quality manifest by the splicing processes undergone by the bearer
Cellular Cell ploidy A cellular quality manifest by the number of genomes that are part of the bearer
Cellular Cell transformative potency
A cellular quality manifest by the capacity of the bearer cell to differentiate to different cell types
Organismal Tissue tone
Organismal Organism reproductive quality
49
How many types of shape are there
notched T-shaped Y-shaped branched unbranched antrose retrose curled curved wiggly squiggly round flat square oblong elliptical ovoid cuboid spherical egg-shaped rod-shaped heart-shaped hellip
How do we define them
How do we compare them
Shapes cannot be organized in a linear scale
Compare problem of classifying RNA structures
50
Standard case monadic qualitiesExamples
ndash E=kidney Q=hypertrophiedndash autodef a kidney which is hypertrophied
We assume that there is more contextual data (not shown)ndash eg genotype environment number of organisms
in study that showed phenotype
Interpretation (with the rest of the database record)ndash all fish in this experiment with a particular
genotype had a hypertrophied kidney at some point in time
51
Who should use PATO
Originallyndash model organism mutant phenotypes
But alsondash ontology-based evolutionary systematicsndash neuroscience BIRNndash clinical uses
bull OMIMbull clinical records (clinical manifestations)bull drug effects chemical effects
ndash to define terms in other ontologiesbull eg diploid cell invasive tumor engineered gene
condensed chromosome
- The Ontology of Experiments + PATO
- Plan
- EXPO
- Slide 4
- EXPO Formalisation of Science
- Slide 6
- Slide 7
- Slide 8
- Suggested Upper Merged Ontology
- SUMO top level
- Suggested Upper Merged Ontology
- SUMO Structure
- SUMO+Domain Ontology
- Slide 14
- Slide 15
- advantages of SUMO
- problems with SUMO as Upper-Level
- Slide 18
- Slide 19
- Slide 20
- Slide 21
- OBI
- Overview of the Ontology of Biomedical Investigations
- OBI neacutee FuGO
- Motivation for OBI
- Emerging FuGO Design Principles
- OBI Collaborating Communities
- Slide 28
- Slide 29
- FuGO - Top Level Universals
- Slide 31
- Slide 32
- Basic Formal Ontology
- Three dichotomies
- instance vs type
- BFO
- Slide 37
- Slide 38
- Unifying goal integration
- Some thoughts on the ontology itself
- Itrsquos all about the definitions
- Old PATO Entity ndash Attribute ndash Value Eye ndash Red ndash Dark
- What a quality is NOT
- Some examples of qualities
- Slide 45
- Qualities are dependent entities
- Slide 48
- How many types of shape are there
- Standard case monadic qualities
- Who should use PATO
-
37
BFO
ContinuantOccurrent(Process)
IndependentContinuant
(molecule cell organorganism)
DependentContinuant
(quality functiondisease)
Functioning Side-Effect Stochastic Process
38
BFO
ContinuantOccurrent(Process)
IndependentContinuant
(molecule cell organorganism)
PATO Functioning Side-Effect Stochastic Process
39
Unifying goal integration
Integrating datandash within and across these domainsndash across levels of granularityndash across different perspectives
Requiresndash Rigorous formal definitions in both ontologies
and annotation schemas
40
Some thoughts on the ontology itself
Outlinendash Definitions
bull how do we define PATO termsbull what exactly is it wersquore defining
ndash is_a hierarchybull what are the top-level distinctionsbull what are the finer grained distinctions
ndash shapes and colors
41
Itrsquos all about the definitions
OBO Foundry Principlendash Definitions should describe things in reality
not how terms are usedbull definitions should not use the word lsquodescribingrsquo
Scope of PATO = Phenotypic qualities
42
Old PATOEntity ndash Attribute ndash Value
Eye ndash Red ndash Dark
New PATOEntity ndash Quality
Eye ndash Red Eye ndash Dark Red
Dark Red is_a Red
43
What a quality is NOT
Qualities are not measurementsndash Instances of qualities exist independently of their
measurementsndash Qualities can have zero or more measurements
These are not the names of qualitiesndash percentagendash processndash abnormalndash high
44
Some examples of qualities
The particular redness of the left eye of a single individual flyndash An instance of a quality type
The color lsquoredrsquondash A quality type
Note the eye does not instantiate lsquoredrsquo
PATO represents quality types (universals)ndash PATO definitions can be used to classify quality
instances by the types they instantiate
45
the particular case ofredness (of a particularfly eye)
the type ldquoredrdquo
instantiates
an instance of an eye(in a particular fly)
the type ldquoeyerdquo
instantiates
inheresin (is aquality ofhas_bearer)
46
Qualities are dependent entities
Qualities require bearersndash Bearers can be physical objects or processes
Examplendash A shape requires a physical object to bear itndash If the physical object ceases to exist (eg it
decomposes) then the shape ceases to exist
48
Scale Bearer Quality Definition (proposed)
Physical Continuant Mass Equivalent to the sum of the mass of the parts of the bearer (mass at the particle level is primitiveoutwith PATO)
Physical Continuant Opacity An optical quality manifest by the capacity of the bearer to block light
PhysChem Liquid Concentration A compositional relational quality manifest by the relative quantity of some chemical type contained by the bearer
Molecular Gene splicing quality manifest by the splicing processes undergone by the bearer
Cellular Cell ploidy A cellular quality manifest by the number of genomes that are part of the bearer
Cellular Cell transformative potency
A cellular quality manifest by the capacity of the bearer cell to differentiate to different cell types
Organismal Tissue tone
Organismal Organism reproductive quality
49
How many types of shape are there
notched T-shaped Y-shaped branched unbranched antrose retrose curled curved wiggly squiggly round flat square oblong elliptical ovoid cuboid spherical egg-shaped rod-shaped heart-shaped hellip
How do we define them
How do we compare them
Shapes cannot be organized in a linear scale
Compare problem of classifying RNA structures
50
Standard case monadic qualitiesExamples
ndash E=kidney Q=hypertrophiedndash autodef a kidney which is hypertrophied
We assume that there is more contextual data (not shown)ndash eg genotype environment number of organisms
in study that showed phenotype
Interpretation (with the rest of the database record)ndash all fish in this experiment with a particular
genotype had a hypertrophied kidney at some point in time
51
Who should use PATO
Originallyndash model organism mutant phenotypes
But alsondash ontology-based evolutionary systematicsndash neuroscience BIRNndash clinical uses
bull OMIMbull clinical records (clinical manifestations)bull drug effects chemical effects
ndash to define terms in other ontologiesbull eg diploid cell invasive tumor engineered gene
condensed chromosome
- The Ontology of Experiments + PATO
- Plan
- EXPO
- Slide 4
- EXPO Formalisation of Science
- Slide 6
- Slide 7
- Slide 8
- Suggested Upper Merged Ontology
- SUMO top level
- Suggested Upper Merged Ontology
- SUMO Structure
- SUMO+Domain Ontology
- Slide 14
- Slide 15
- advantages of SUMO
- problems with SUMO as Upper-Level
- Slide 18
- Slide 19
- Slide 20
- Slide 21
- OBI
- Overview of the Ontology of Biomedical Investigations
- OBI neacutee FuGO
- Motivation for OBI
- Emerging FuGO Design Principles
- OBI Collaborating Communities
- Slide 28
- Slide 29
- FuGO - Top Level Universals
- Slide 31
- Slide 32
- Basic Formal Ontology
- Three dichotomies
- instance vs type
- BFO
- Slide 37
- Slide 38
- Unifying goal integration
- Some thoughts on the ontology itself
- Itrsquos all about the definitions
- Old PATO Entity ndash Attribute ndash Value Eye ndash Red ndash Dark
- What a quality is NOT
- Some examples of qualities
- Slide 45
- Qualities are dependent entities
- Slide 48
- How many types of shape are there
- Standard case monadic qualities
- Who should use PATO
-
38
BFO
ContinuantOccurrent(Process)
IndependentContinuant
(molecule cell organorganism)
PATO Functioning Side-Effect Stochastic Process
39
Unifying goal integration
Integrating datandash within and across these domainsndash across levels of granularityndash across different perspectives
Requiresndash Rigorous formal definitions in both ontologies
and annotation schemas
40
Some thoughts on the ontology itself
Outlinendash Definitions
bull how do we define PATO termsbull what exactly is it wersquore defining
ndash is_a hierarchybull what are the top-level distinctionsbull what are the finer grained distinctions
ndash shapes and colors
41
Itrsquos all about the definitions
OBO Foundry Principlendash Definitions should describe things in reality
not how terms are usedbull definitions should not use the word lsquodescribingrsquo
Scope of PATO = Phenotypic qualities
42
Old PATOEntity ndash Attribute ndash Value
Eye ndash Red ndash Dark
New PATOEntity ndash Quality
Eye ndash Red Eye ndash Dark Red
Dark Red is_a Red
43
What a quality is NOT
Qualities are not measurementsndash Instances of qualities exist independently of their
measurementsndash Qualities can have zero or more measurements
These are not the names of qualitiesndash percentagendash processndash abnormalndash high
44
Some examples of qualities
The particular redness of the left eye of a single individual flyndash An instance of a quality type
The color lsquoredrsquondash A quality type
Note the eye does not instantiate lsquoredrsquo
PATO represents quality types (universals)ndash PATO definitions can be used to classify quality
instances by the types they instantiate
45
the particular case ofredness (of a particularfly eye)
the type ldquoredrdquo
instantiates
an instance of an eye(in a particular fly)
the type ldquoeyerdquo
instantiates
inheresin (is aquality ofhas_bearer)
46
Qualities are dependent entities
Qualities require bearersndash Bearers can be physical objects or processes
Examplendash A shape requires a physical object to bear itndash If the physical object ceases to exist (eg it
decomposes) then the shape ceases to exist
48
Scale Bearer Quality Definition (proposed)
Physical Continuant Mass Equivalent to the sum of the mass of the parts of the bearer (mass at the particle level is primitiveoutwith PATO)
Physical Continuant Opacity An optical quality manifest by the capacity of the bearer to block light
PhysChem Liquid Concentration A compositional relational quality manifest by the relative quantity of some chemical type contained by the bearer
Molecular Gene splicing quality manifest by the splicing processes undergone by the bearer
Cellular Cell ploidy A cellular quality manifest by the number of genomes that are part of the bearer
Cellular Cell transformative potency
A cellular quality manifest by the capacity of the bearer cell to differentiate to different cell types
Organismal Tissue tone
Organismal Organism reproductive quality
49
How many types of shape are there
notched T-shaped Y-shaped branched unbranched antrose retrose curled curved wiggly squiggly round flat square oblong elliptical ovoid cuboid spherical egg-shaped rod-shaped heart-shaped hellip
How do we define them
How do we compare them
Shapes cannot be organized in a linear scale
Compare problem of classifying RNA structures
50
Standard case monadic qualitiesExamples
ndash E=kidney Q=hypertrophiedndash autodef a kidney which is hypertrophied
We assume that there is more contextual data (not shown)ndash eg genotype environment number of organisms
in study that showed phenotype
Interpretation (with the rest of the database record)ndash all fish in this experiment with a particular
genotype had a hypertrophied kidney at some point in time
51
Who should use PATO
Originallyndash model organism mutant phenotypes
But alsondash ontology-based evolutionary systematicsndash neuroscience BIRNndash clinical uses
bull OMIMbull clinical records (clinical manifestations)bull drug effects chemical effects
ndash to define terms in other ontologiesbull eg diploid cell invasive tumor engineered gene
condensed chromosome
- The Ontology of Experiments + PATO
- Plan
- EXPO
- Slide 4
- EXPO Formalisation of Science
- Slide 6
- Slide 7
- Slide 8
- Suggested Upper Merged Ontology
- SUMO top level
- Suggested Upper Merged Ontology
- SUMO Structure
- SUMO+Domain Ontology
- Slide 14
- Slide 15
- advantages of SUMO
- problems with SUMO as Upper-Level
- Slide 18
- Slide 19
- Slide 20
- Slide 21
- OBI
- Overview of the Ontology of Biomedical Investigations
- OBI neacutee FuGO
- Motivation for OBI
- Emerging FuGO Design Principles
- OBI Collaborating Communities
- Slide 28
- Slide 29
- FuGO - Top Level Universals
- Slide 31
- Slide 32
- Basic Formal Ontology
- Three dichotomies
- instance vs type
- BFO
- Slide 37
- Slide 38
- Unifying goal integration
- Some thoughts on the ontology itself
- Itrsquos all about the definitions
- Old PATO Entity ndash Attribute ndash Value Eye ndash Red ndash Dark
- What a quality is NOT
- Some examples of qualities
- Slide 45
- Qualities are dependent entities
- Slide 48
- How many types of shape are there
- Standard case monadic qualities
- Who should use PATO
-
39
Unifying goal integration
Integrating datandash within and across these domainsndash across levels of granularityndash across different perspectives
Requiresndash Rigorous formal definitions in both ontologies
and annotation schemas
40
Some thoughts on the ontology itself
Outlinendash Definitions
bull how do we define PATO termsbull what exactly is it wersquore defining
ndash is_a hierarchybull what are the top-level distinctionsbull what are the finer grained distinctions
ndash shapes and colors
41
Itrsquos all about the definitions
OBO Foundry Principlendash Definitions should describe things in reality
not how terms are usedbull definitions should not use the word lsquodescribingrsquo
Scope of PATO = Phenotypic qualities
42
Old PATOEntity ndash Attribute ndash Value
Eye ndash Red ndash Dark
New PATOEntity ndash Quality
Eye ndash Red Eye ndash Dark Red
Dark Red is_a Red
43
What a quality is NOT
Qualities are not measurementsndash Instances of qualities exist independently of their
measurementsndash Qualities can have zero or more measurements
These are not the names of qualitiesndash percentagendash processndash abnormalndash high
44
Some examples of qualities
The particular redness of the left eye of a single individual flyndash An instance of a quality type
The color lsquoredrsquondash A quality type
Note the eye does not instantiate lsquoredrsquo
PATO represents quality types (universals)ndash PATO definitions can be used to classify quality
instances by the types they instantiate
45
the particular case ofredness (of a particularfly eye)
the type ldquoredrdquo
instantiates
an instance of an eye(in a particular fly)
the type ldquoeyerdquo
instantiates
inheresin (is aquality ofhas_bearer)
46
Qualities are dependent entities
Qualities require bearersndash Bearers can be physical objects or processes
Examplendash A shape requires a physical object to bear itndash If the physical object ceases to exist (eg it
decomposes) then the shape ceases to exist
48
Scale Bearer Quality Definition (proposed)
Physical Continuant Mass Equivalent to the sum of the mass of the parts of the bearer (mass at the particle level is primitiveoutwith PATO)
Physical Continuant Opacity An optical quality manifest by the capacity of the bearer to block light
PhysChem Liquid Concentration A compositional relational quality manifest by the relative quantity of some chemical type contained by the bearer
Molecular Gene splicing quality manifest by the splicing processes undergone by the bearer
Cellular Cell ploidy A cellular quality manifest by the number of genomes that are part of the bearer
Cellular Cell transformative potency
A cellular quality manifest by the capacity of the bearer cell to differentiate to different cell types
Organismal Tissue tone
Organismal Organism reproductive quality
49
How many types of shape are there
notched T-shaped Y-shaped branched unbranched antrose retrose curled curved wiggly squiggly round flat square oblong elliptical ovoid cuboid spherical egg-shaped rod-shaped heart-shaped hellip
How do we define them
How do we compare them
Shapes cannot be organized in a linear scale
Compare problem of classifying RNA structures
50
Standard case monadic qualitiesExamples
ndash E=kidney Q=hypertrophiedndash autodef a kidney which is hypertrophied
We assume that there is more contextual data (not shown)ndash eg genotype environment number of organisms
in study that showed phenotype
Interpretation (with the rest of the database record)ndash all fish in this experiment with a particular
genotype had a hypertrophied kidney at some point in time
51
Who should use PATO
Originallyndash model organism mutant phenotypes
But alsondash ontology-based evolutionary systematicsndash neuroscience BIRNndash clinical uses
bull OMIMbull clinical records (clinical manifestations)bull drug effects chemical effects
ndash to define terms in other ontologiesbull eg diploid cell invasive tumor engineered gene
condensed chromosome
- The Ontology of Experiments + PATO
- Plan
- EXPO
- Slide 4
- EXPO Formalisation of Science
- Slide 6
- Slide 7
- Slide 8
- Suggested Upper Merged Ontology
- SUMO top level
- Suggested Upper Merged Ontology
- SUMO Structure
- SUMO+Domain Ontology
- Slide 14
- Slide 15
- advantages of SUMO
- problems with SUMO as Upper-Level
- Slide 18
- Slide 19
- Slide 20
- Slide 21
- OBI
- Overview of the Ontology of Biomedical Investigations
- OBI neacutee FuGO
- Motivation for OBI
- Emerging FuGO Design Principles
- OBI Collaborating Communities
- Slide 28
- Slide 29
- FuGO - Top Level Universals
- Slide 31
- Slide 32
- Basic Formal Ontology
- Three dichotomies
- instance vs type
- BFO
- Slide 37
- Slide 38
- Unifying goal integration
- Some thoughts on the ontology itself
- Itrsquos all about the definitions
- Old PATO Entity ndash Attribute ndash Value Eye ndash Red ndash Dark
- What a quality is NOT
- Some examples of qualities
- Slide 45
- Qualities are dependent entities
- Slide 48
- How many types of shape are there
- Standard case monadic qualities
- Who should use PATO
-
40
Some thoughts on the ontology itself
Outlinendash Definitions
bull how do we define PATO termsbull what exactly is it wersquore defining
ndash is_a hierarchybull what are the top-level distinctionsbull what are the finer grained distinctions
ndash shapes and colors
41
Itrsquos all about the definitions
OBO Foundry Principlendash Definitions should describe things in reality
not how terms are usedbull definitions should not use the word lsquodescribingrsquo
Scope of PATO = Phenotypic qualities
42
Old PATOEntity ndash Attribute ndash Value
Eye ndash Red ndash Dark
New PATOEntity ndash Quality
Eye ndash Red Eye ndash Dark Red
Dark Red is_a Red
43
What a quality is NOT
Qualities are not measurementsndash Instances of qualities exist independently of their
measurementsndash Qualities can have zero or more measurements
These are not the names of qualitiesndash percentagendash processndash abnormalndash high
44
Some examples of qualities
The particular redness of the left eye of a single individual flyndash An instance of a quality type
The color lsquoredrsquondash A quality type
Note the eye does not instantiate lsquoredrsquo
PATO represents quality types (universals)ndash PATO definitions can be used to classify quality
instances by the types they instantiate
45
the particular case ofredness (of a particularfly eye)
the type ldquoredrdquo
instantiates
an instance of an eye(in a particular fly)
the type ldquoeyerdquo
instantiates
inheresin (is aquality ofhas_bearer)
46
Qualities are dependent entities
Qualities require bearersndash Bearers can be physical objects or processes
Examplendash A shape requires a physical object to bear itndash If the physical object ceases to exist (eg it
decomposes) then the shape ceases to exist
48
Scale Bearer Quality Definition (proposed)
Physical Continuant Mass Equivalent to the sum of the mass of the parts of the bearer (mass at the particle level is primitiveoutwith PATO)
Physical Continuant Opacity An optical quality manifest by the capacity of the bearer to block light
PhysChem Liquid Concentration A compositional relational quality manifest by the relative quantity of some chemical type contained by the bearer
Molecular Gene splicing quality manifest by the splicing processes undergone by the bearer
Cellular Cell ploidy A cellular quality manifest by the number of genomes that are part of the bearer
Cellular Cell transformative potency
A cellular quality manifest by the capacity of the bearer cell to differentiate to different cell types
Organismal Tissue tone
Organismal Organism reproductive quality
49
How many types of shape are there
notched T-shaped Y-shaped branched unbranched antrose retrose curled curved wiggly squiggly round flat square oblong elliptical ovoid cuboid spherical egg-shaped rod-shaped heart-shaped hellip
How do we define them
How do we compare them
Shapes cannot be organized in a linear scale
Compare problem of classifying RNA structures
50
Standard case monadic qualitiesExamples
ndash E=kidney Q=hypertrophiedndash autodef a kidney which is hypertrophied
We assume that there is more contextual data (not shown)ndash eg genotype environment number of organisms
in study that showed phenotype
Interpretation (with the rest of the database record)ndash all fish in this experiment with a particular
genotype had a hypertrophied kidney at some point in time
51
Who should use PATO
Originallyndash model organism mutant phenotypes
But alsondash ontology-based evolutionary systematicsndash neuroscience BIRNndash clinical uses
bull OMIMbull clinical records (clinical manifestations)bull drug effects chemical effects
ndash to define terms in other ontologiesbull eg diploid cell invasive tumor engineered gene
condensed chromosome
- The Ontology of Experiments + PATO
- Plan
- EXPO
- Slide 4
- EXPO Formalisation of Science
- Slide 6
- Slide 7
- Slide 8
- Suggested Upper Merged Ontology
- SUMO top level
- Suggested Upper Merged Ontology
- SUMO Structure
- SUMO+Domain Ontology
- Slide 14
- Slide 15
- advantages of SUMO
- problems with SUMO as Upper-Level
- Slide 18
- Slide 19
- Slide 20
- Slide 21
- OBI
- Overview of the Ontology of Biomedical Investigations
- OBI neacutee FuGO
- Motivation for OBI
- Emerging FuGO Design Principles
- OBI Collaborating Communities
- Slide 28
- Slide 29
- FuGO - Top Level Universals
- Slide 31
- Slide 32
- Basic Formal Ontology
- Three dichotomies
- instance vs type
- BFO
- Slide 37
- Slide 38
- Unifying goal integration
- Some thoughts on the ontology itself
- Itrsquos all about the definitions
- Old PATO Entity ndash Attribute ndash Value Eye ndash Red ndash Dark
- What a quality is NOT
- Some examples of qualities
- Slide 45
- Qualities are dependent entities
- Slide 48
- How many types of shape are there
- Standard case monadic qualities
- Who should use PATO
-
41
Itrsquos all about the definitions
OBO Foundry Principlendash Definitions should describe things in reality
not how terms are usedbull definitions should not use the word lsquodescribingrsquo
Scope of PATO = Phenotypic qualities
42
Old PATOEntity ndash Attribute ndash Value
Eye ndash Red ndash Dark
New PATOEntity ndash Quality
Eye ndash Red Eye ndash Dark Red
Dark Red is_a Red
43
What a quality is NOT
Qualities are not measurementsndash Instances of qualities exist independently of their
measurementsndash Qualities can have zero or more measurements
These are not the names of qualitiesndash percentagendash processndash abnormalndash high
44
Some examples of qualities
The particular redness of the left eye of a single individual flyndash An instance of a quality type
The color lsquoredrsquondash A quality type
Note the eye does not instantiate lsquoredrsquo
PATO represents quality types (universals)ndash PATO definitions can be used to classify quality
instances by the types they instantiate
45
the particular case ofredness (of a particularfly eye)
the type ldquoredrdquo
instantiates
an instance of an eye(in a particular fly)
the type ldquoeyerdquo
instantiates
inheresin (is aquality ofhas_bearer)
46
Qualities are dependent entities
Qualities require bearersndash Bearers can be physical objects or processes
Examplendash A shape requires a physical object to bear itndash If the physical object ceases to exist (eg it
decomposes) then the shape ceases to exist
48
Scale Bearer Quality Definition (proposed)
Physical Continuant Mass Equivalent to the sum of the mass of the parts of the bearer (mass at the particle level is primitiveoutwith PATO)
Physical Continuant Opacity An optical quality manifest by the capacity of the bearer to block light
PhysChem Liquid Concentration A compositional relational quality manifest by the relative quantity of some chemical type contained by the bearer
Molecular Gene splicing quality manifest by the splicing processes undergone by the bearer
Cellular Cell ploidy A cellular quality manifest by the number of genomes that are part of the bearer
Cellular Cell transformative potency
A cellular quality manifest by the capacity of the bearer cell to differentiate to different cell types
Organismal Tissue tone
Organismal Organism reproductive quality
49
How many types of shape are there
notched T-shaped Y-shaped branched unbranched antrose retrose curled curved wiggly squiggly round flat square oblong elliptical ovoid cuboid spherical egg-shaped rod-shaped heart-shaped hellip
How do we define them
How do we compare them
Shapes cannot be organized in a linear scale
Compare problem of classifying RNA structures
50
Standard case monadic qualitiesExamples
ndash E=kidney Q=hypertrophiedndash autodef a kidney which is hypertrophied
We assume that there is more contextual data (not shown)ndash eg genotype environment number of organisms
in study that showed phenotype
Interpretation (with the rest of the database record)ndash all fish in this experiment with a particular
genotype had a hypertrophied kidney at some point in time
51
Who should use PATO
Originallyndash model organism mutant phenotypes
But alsondash ontology-based evolutionary systematicsndash neuroscience BIRNndash clinical uses
bull OMIMbull clinical records (clinical manifestations)bull drug effects chemical effects
ndash to define terms in other ontologiesbull eg diploid cell invasive tumor engineered gene
condensed chromosome
- The Ontology of Experiments + PATO
- Plan
- EXPO
- Slide 4
- EXPO Formalisation of Science
- Slide 6
- Slide 7
- Slide 8
- Suggested Upper Merged Ontology
- SUMO top level
- Suggested Upper Merged Ontology
- SUMO Structure
- SUMO+Domain Ontology
- Slide 14
- Slide 15
- advantages of SUMO
- problems with SUMO as Upper-Level
- Slide 18
- Slide 19
- Slide 20
- Slide 21
- OBI
- Overview of the Ontology of Biomedical Investigations
- OBI neacutee FuGO
- Motivation for OBI
- Emerging FuGO Design Principles
- OBI Collaborating Communities
- Slide 28
- Slide 29
- FuGO - Top Level Universals
- Slide 31
- Slide 32
- Basic Formal Ontology
- Three dichotomies
- instance vs type
- BFO
- Slide 37
- Slide 38
- Unifying goal integration
- Some thoughts on the ontology itself
- Itrsquos all about the definitions
- Old PATO Entity ndash Attribute ndash Value Eye ndash Red ndash Dark
- What a quality is NOT
- Some examples of qualities
- Slide 45
- Qualities are dependent entities
- Slide 48
- How many types of shape are there
- Standard case monadic qualities
- Who should use PATO
-
42
Old PATOEntity ndash Attribute ndash Value
Eye ndash Red ndash Dark
New PATOEntity ndash Quality
Eye ndash Red Eye ndash Dark Red
Dark Red is_a Red
43
What a quality is NOT
Qualities are not measurementsndash Instances of qualities exist independently of their
measurementsndash Qualities can have zero or more measurements
These are not the names of qualitiesndash percentagendash processndash abnormalndash high
44
Some examples of qualities
The particular redness of the left eye of a single individual flyndash An instance of a quality type
The color lsquoredrsquondash A quality type
Note the eye does not instantiate lsquoredrsquo
PATO represents quality types (universals)ndash PATO definitions can be used to classify quality
instances by the types they instantiate
45
the particular case ofredness (of a particularfly eye)
the type ldquoredrdquo
instantiates
an instance of an eye(in a particular fly)
the type ldquoeyerdquo
instantiates
inheresin (is aquality ofhas_bearer)
46
Qualities are dependent entities
Qualities require bearersndash Bearers can be physical objects or processes
Examplendash A shape requires a physical object to bear itndash If the physical object ceases to exist (eg it
decomposes) then the shape ceases to exist
48
Scale Bearer Quality Definition (proposed)
Physical Continuant Mass Equivalent to the sum of the mass of the parts of the bearer (mass at the particle level is primitiveoutwith PATO)
Physical Continuant Opacity An optical quality manifest by the capacity of the bearer to block light
PhysChem Liquid Concentration A compositional relational quality manifest by the relative quantity of some chemical type contained by the bearer
Molecular Gene splicing quality manifest by the splicing processes undergone by the bearer
Cellular Cell ploidy A cellular quality manifest by the number of genomes that are part of the bearer
Cellular Cell transformative potency
A cellular quality manifest by the capacity of the bearer cell to differentiate to different cell types
Organismal Tissue tone
Organismal Organism reproductive quality
49
How many types of shape are there
notched T-shaped Y-shaped branched unbranched antrose retrose curled curved wiggly squiggly round flat square oblong elliptical ovoid cuboid spherical egg-shaped rod-shaped heart-shaped hellip
How do we define them
How do we compare them
Shapes cannot be organized in a linear scale
Compare problem of classifying RNA structures
50
Standard case monadic qualitiesExamples
ndash E=kidney Q=hypertrophiedndash autodef a kidney which is hypertrophied
We assume that there is more contextual data (not shown)ndash eg genotype environment number of organisms
in study that showed phenotype
Interpretation (with the rest of the database record)ndash all fish in this experiment with a particular
genotype had a hypertrophied kidney at some point in time
51
Who should use PATO
Originallyndash model organism mutant phenotypes
But alsondash ontology-based evolutionary systematicsndash neuroscience BIRNndash clinical uses
bull OMIMbull clinical records (clinical manifestations)bull drug effects chemical effects
ndash to define terms in other ontologiesbull eg diploid cell invasive tumor engineered gene
condensed chromosome
- The Ontology of Experiments + PATO
- Plan
- EXPO
- Slide 4
- EXPO Formalisation of Science
- Slide 6
- Slide 7
- Slide 8
- Suggested Upper Merged Ontology
- SUMO top level
- Suggested Upper Merged Ontology
- SUMO Structure
- SUMO+Domain Ontology
- Slide 14
- Slide 15
- advantages of SUMO
- problems with SUMO as Upper-Level
- Slide 18
- Slide 19
- Slide 20
- Slide 21
- OBI
- Overview of the Ontology of Biomedical Investigations
- OBI neacutee FuGO
- Motivation for OBI
- Emerging FuGO Design Principles
- OBI Collaborating Communities
- Slide 28
- Slide 29
- FuGO - Top Level Universals
- Slide 31
- Slide 32
- Basic Formal Ontology
- Three dichotomies
- instance vs type
- BFO
- Slide 37
- Slide 38
- Unifying goal integration
- Some thoughts on the ontology itself
- Itrsquos all about the definitions
- Old PATO Entity ndash Attribute ndash Value Eye ndash Red ndash Dark
- What a quality is NOT
- Some examples of qualities
- Slide 45
- Qualities are dependent entities
- Slide 48
- How many types of shape are there
- Standard case monadic qualities
- Who should use PATO
-
43
What a quality is NOT
Qualities are not measurementsndash Instances of qualities exist independently of their
measurementsndash Qualities can have zero or more measurements
These are not the names of qualitiesndash percentagendash processndash abnormalndash high
44
Some examples of qualities
The particular redness of the left eye of a single individual flyndash An instance of a quality type
The color lsquoredrsquondash A quality type
Note the eye does not instantiate lsquoredrsquo
PATO represents quality types (universals)ndash PATO definitions can be used to classify quality
instances by the types they instantiate
45
the particular case ofredness (of a particularfly eye)
the type ldquoredrdquo
instantiates
an instance of an eye(in a particular fly)
the type ldquoeyerdquo
instantiates
inheresin (is aquality ofhas_bearer)
46
Qualities are dependent entities
Qualities require bearersndash Bearers can be physical objects or processes
Examplendash A shape requires a physical object to bear itndash If the physical object ceases to exist (eg it
decomposes) then the shape ceases to exist
48
Scale Bearer Quality Definition (proposed)
Physical Continuant Mass Equivalent to the sum of the mass of the parts of the bearer (mass at the particle level is primitiveoutwith PATO)
Physical Continuant Opacity An optical quality manifest by the capacity of the bearer to block light
PhysChem Liquid Concentration A compositional relational quality manifest by the relative quantity of some chemical type contained by the bearer
Molecular Gene splicing quality manifest by the splicing processes undergone by the bearer
Cellular Cell ploidy A cellular quality manifest by the number of genomes that are part of the bearer
Cellular Cell transformative potency
A cellular quality manifest by the capacity of the bearer cell to differentiate to different cell types
Organismal Tissue tone
Organismal Organism reproductive quality
49
How many types of shape are there
notched T-shaped Y-shaped branched unbranched antrose retrose curled curved wiggly squiggly round flat square oblong elliptical ovoid cuboid spherical egg-shaped rod-shaped heart-shaped hellip
How do we define them
How do we compare them
Shapes cannot be organized in a linear scale
Compare problem of classifying RNA structures
50
Standard case monadic qualitiesExamples
ndash E=kidney Q=hypertrophiedndash autodef a kidney which is hypertrophied
We assume that there is more contextual data (not shown)ndash eg genotype environment number of organisms
in study that showed phenotype
Interpretation (with the rest of the database record)ndash all fish in this experiment with a particular
genotype had a hypertrophied kidney at some point in time
51
Who should use PATO
Originallyndash model organism mutant phenotypes
But alsondash ontology-based evolutionary systematicsndash neuroscience BIRNndash clinical uses
bull OMIMbull clinical records (clinical manifestations)bull drug effects chemical effects
ndash to define terms in other ontologiesbull eg diploid cell invasive tumor engineered gene
condensed chromosome
- The Ontology of Experiments + PATO
- Plan
- EXPO
- Slide 4
- EXPO Formalisation of Science
- Slide 6
- Slide 7
- Slide 8
- Suggested Upper Merged Ontology
- SUMO top level
- Suggested Upper Merged Ontology
- SUMO Structure
- SUMO+Domain Ontology
- Slide 14
- Slide 15
- advantages of SUMO
- problems with SUMO as Upper-Level
- Slide 18
- Slide 19
- Slide 20
- Slide 21
- OBI
- Overview of the Ontology of Biomedical Investigations
- OBI neacutee FuGO
- Motivation for OBI
- Emerging FuGO Design Principles
- OBI Collaborating Communities
- Slide 28
- Slide 29
- FuGO - Top Level Universals
- Slide 31
- Slide 32
- Basic Formal Ontology
- Three dichotomies
- instance vs type
- BFO
- Slide 37
- Slide 38
- Unifying goal integration
- Some thoughts on the ontology itself
- Itrsquos all about the definitions
- Old PATO Entity ndash Attribute ndash Value Eye ndash Red ndash Dark
- What a quality is NOT
- Some examples of qualities
- Slide 45
- Qualities are dependent entities
- Slide 48
- How many types of shape are there
- Standard case monadic qualities
- Who should use PATO
-
44
Some examples of qualities
The particular redness of the left eye of a single individual flyndash An instance of a quality type
The color lsquoredrsquondash A quality type
Note the eye does not instantiate lsquoredrsquo
PATO represents quality types (universals)ndash PATO definitions can be used to classify quality
instances by the types they instantiate
45
the particular case ofredness (of a particularfly eye)
the type ldquoredrdquo
instantiates
an instance of an eye(in a particular fly)
the type ldquoeyerdquo
instantiates
inheresin (is aquality ofhas_bearer)
46
Qualities are dependent entities
Qualities require bearersndash Bearers can be physical objects or processes
Examplendash A shape requires a physical object to bear itndash If the physical object ceases to exist (eg it
decomposes) then the shape ceases to exist
48
Scale Bearer Quality Definition (proposed)
Physical Continuant Mass Equivalent to the sum of the mass of the parts of the bearer (mass at the particle level is primitiveoutwith PATO)
Physical Continuant Opacity An optical quality manifest by the capacity of the bearer to block light
PhysChem Liquid Concentration A compositional relational quality manifest by the relative quantity of some chemical type contained by the bearer
Molecular Gene splicing quality manifest by the splicing processes undergone by the bearer
Cellular Cell ploidy A cellular quality manifest by the number of genomes that are part of the bearer
Cellular Cell transformative potency
A cellular quality manifest by the capacity of the bearer cell to differentiate to different cell types
Organismal Tissue tone
Organismal Organism reproductive quality
49
How many types of shape are there
notched T-shaped Y-shaped branched unbranched antrose retrose curled curved wiggly squiggly round flat square oblong elliptical ovoid cuboid spherical egg-shaped rod-shaped heart-shaped hellip
How do we define them
How do we compare them
Shapes cannot be organized in a linear scale
Compare problem of classifying RNA structures
50
Standard case monadic qualitiesExamples
ndash E=kidney Q=hypertrophiedndash autodef a kidney which is hypertrophied
We assume that there is more contextual data (not shown)ndash eg genotype environment number of organisms
in study that showed phenotype
Interpretation (with the rest of the database record)ndash all fish in this experiment with a particular
genotype had a hypertrophied kidney at some point in time
51
Who should use PATO
Originallyndash model organism mutant phenotypes
But alsondash ontology-based evolutionary systematicsndash neuroscience BIRNndash clinical uses
bull OMIMbull clinical records (clinical manifestations)bull drug effects chemical effects
ndash to define terms in other ontologiesbull eg diploid cell invasive tumor engineered gene
condensed chromosome
- The Ontology of Experiments + PATO
- Plan
- EXPO
- Slide 4
- EXPO Formalisation of Science
- Slide 6
- Slide 7
- Slide 8
- Suggested Upper Merged Ontology
- SUMO top level
- Suggested Upper Merged Ontology
- SUMO Structure
- SUMO+Domain Ontology
- Slide 14
- Slide 15
- advantages of SUMO
- problems with SUMO as Upper-Level
- Slide 18
- Slide 19
- Slide 20
- Slide 21
- OBI
- Overview of the Ontology of Biomedical Investigations
- OBI neacutee FuGO
- Motivation for OBI
- Emerging FuGO Design Principles
- OBI Collaborating Communities
- Slide 28
- Slide 29
- FuGO - Top Level Universals
- Slide 31
- Slide 32
- Basic Formal Ontology
- Three dichotomies
- instance vs type
- BFO
- Slide 37
- Slide 38
- Unifying goal integration
- Some thoughts on the ontology itself
- Itrsquos all about the definitions
- Old PATO Entity ndash Attribute ndash Value Eye ndash Red ndash Dark
- What a quality is NOT
- Some examples of qualities
- Slide 45
- Qualities are dependent entities
- Slide 48
- How many types of shape are there
- Standard case monadic qualities
- Who should use PATO
-
45
the particular case ofredness (of a particularfly eye)
the type ldquoredrdquo
instantiates
an instance of an eye(in a particular fly)
the type ldquoeyerdquo
instantiates
inheresin (is aquality ofhas_bearer)
46
Qualities are dependent entities
Qualities require bearersndash Bearers can be physical objects or processes
Examplendash A shape requires a physical object to bear itndash If the physical object ceases to exist (eg it
decomposes) then the shape ceases to exist
48
Scale Bearer Quality Definition (proposed)
Physical Continuant Mass Equivalent to the sum of the mass of the parts of the bearer (mass at the particle level is primitiveoutwith PATO)
Physical Continuant Opacity An optical quality manifest by the capacity of the bearer to block light
PhysChem Liquid Concentration A compositional relational quality manifest by the relative quantity of some chemical type contained by the bearer
Molecular Gene splicing quality manifest by the splicing processes undergone by the bearer
Cellular Cell ploidy A cellular quality manifest by the number of genomes that are part of the bearer
Cellular Cell transformative potency
A cellular quality manifest by the capacity of the bearer cell to differentiate to different cell types
Organismal Tissue tone
Organismal Organism reproductive quality
49
How many types of shape are there
notched T-shaped Y-shaped branched unbranched antrose retrose curled curved wiggly squiggly round flat square oblong elliptical ovoid cuboid spherical egg-shaped rod-shaped heart-shaped hellip
How do we define them
How do we compare them
Shapes cannot be organized in a linear scale
Compare problem of classifying RNA structures
50
Standard case monadic qualitiesExamples
ndash E=kidney Q=hypertrophiedndash autodef a kidney which is hypertrophied
We assume that there is more contextual data (not shown)ndash eg genotype environment number of organisms
in study that showed phenotype
Interpretation (with the rest of the database record)ndash all fish in this experiment with a particular
genotype had a hypertrophied kidney at some point in time
51
Who should use PATO
Originallyndash model organism mutant phenotypes
But alsondash ontology-based evolutionary systematicsndash neuroscience BIRNndash clinical uses
bull OMIMbull clinical records (clinical manifestations)bull drug effects chemical effects
ndash to define terms in other ontologiesbull eg diploid cell invasive tumor engineered gene
condensed chromosome
- The Ontology of Experiments + PATO
- Plan
- EXPO
- Slide 4
- EXPO Formalisation of Science
- Slide 6
- Slide 7
- Slide 8
- Suggested Upper Merged Ontology
- SUMO top level
- Suggested Upper Merged Ontology
- SUMO Structure
- SUMO+Domain Ontology
- Slide 14
- Slide 15
- advantages of SUMO
- problems with SUMO as Upper-Level
- Slide 18
- Slide 19
- Slide 20
- Slide 21
- OBI
- Overview of the Ontology of Biomedical Investigations
- OBI neacutee FuGO
- Motivation for OBI
- Emerging FuGO Design Principles
- OBI Collaborating Communities
- Slide 28
- Slide 29
- FuGO - Top Level Universals
- Slide 31
- Slide 32
- Basic Formal Ontology
- Three dichotomies
- instance vs type
- BFO
- Slide 37
- Slide 38
- Unifying goal integration
- Some thoughts on the ontology itself
- Itrsquos all about the definitions
- Old PATO Entity ndash Attribute ndash Value Eye ndash Red ndash Dark
- What a quality is NOT
- Some examples of qualities
- Slide 45
- Qualities are dependent entities
- Slide 48
- How many types of shape are there
- Standard case monadic qualities
- Who should use PATO
-
46
Qualities are dependent entities
Qualities require bearersndash Bearers can be physical objects or processes
Examplendash A shape requires a physical object to bear itndash If the physical object ceases to exist (eg it
decomposes) then the shape ceases to exist
48
Scale Bearer Quality Definition (proposed)
Physical Continuant Mass Equivalent to the sum of the mass of the parts of the bearer (mass at the particle level is primitiveoutwith PATO)
Physical Continuant Opacity An optical quality manifest by the capacity of the bearer to block light
PhysChem Liquid Concentration A compositional relational quality manifest by the relative quantity of some chemical type contained by the bearer
Molecular Gene splicing quality manifest by the splicing processes undergone by the bearer
Cellular Cell ploidy A cellular quality manifest by the number of genomes that are part of the bearer
Cellular Cell transformative potency
A cellular quality manifest by the capacity of the bearer cell to differentiate to different cell types
Organismal Tissue tone
Organismal Organism reproductive quality
49
How many types of shape are there
notched T-shaped Y-shaped branched unbranched antrose retrose curled curved wiggly squiggly round flat square oblong elliptical ovoid cuboid spherical egg-shaped rod-shaped heart-shaped hellip
How do we define them
How do we compare them
Shapes cannot be organized in a linear scale
Compare problem of classifying RNA structures
50
Standard case monadic qualitiesExamples
ndash E=kidney Q=hypertrophiedndash autodef a kidney which is hypertrophied
We assume that there is more contextual data (not shown)ndash eg genotype environment number of organisms
in study that showed phenotype
Interpretation (with the rest of the database record)ndash all fish in this experiment with a particular
genotype had a hypertrophied kidney at some point in time
51
Who should use PATO
Originallyndash model organism mutant phenotypes
But alsondash ontology-based evolutionary systematicsndash neuroscience BIRNndash clinical uses
bull OMIMbull clinical records (clinical manifestations)bull drug effects chemical effects
ndash to define terms in other ontologiesbull eg diploid cell invasive tumor engineered gene
condensed chromosome
- The Ontology of Experiments + PATO
- Plan
- EXPO
- Slide 4
- EXPO Formalisation of Science
- Slide 6
- Slide 7
- Slide 8
- Suggested Upper Merged Ontology
- SUMO top level
- Suggested Upper Merged Ontology
- SUMO Structure
- SUMO+Domain Ontology
- Slide 14
- Slide 15
- advantages of SUMO
- problems with SUMO as Upper-Level
- Slide 18
- Slide 19
- Slide 20
- Slide 21
- OBI
- Overview of the Ontology of Biomedical Investigations
- OBI neacutee FuGO
- Motivation for OBI
- Emerging FuGO Design Principles
- OBI Collaborating Communities
- Slide 28
- Slide 29
- FuGO - Top Level Universals
- Slide 31
- Slide 32
- Basic Formal Ontology
- Three dichotomies
- instance vs type
- BFO
- Slide 37
- Slide 38
- Unifying goal integration
- Some thoughts on the ontology itself
- Itrsquos all about the definitions
- Old PATO Entity ndash Attribute ndash Value Eye ndash Red ndash Dark
- What a quality is NOT
- Some examples of qualities
- Slide 45
- Qualities are dependent entities
- Slide 48
- How many types of shape are there
- Standard case monadic qualities
- Who should use PATO
-
48
Scale Bearer Quality Definition (proposed)
Physical Continuant Mass Equivalent to the sum of the mass of the parts of the bearer (mass at the particle level is primitiveoutwith PATO)
Physical Continuant Opacity An optical quality manifest by the capacity of the bearer to block light
PhysChem Liquid Concentration A compositional relational quality manifest by the relative quantity of some chemical type contained by the bearer
Molecular Gene splicing quality manifest by the splicing processes undergone by the bearer
Cellular Cell ploidy A cellular quality manifest by the number of genomes that are part of the bearer
Cellular Cell transformative potency
A cellular quality manifest by the capacity of the bearer cell to differentiate to different cell types
Organismal Tissue tone
Organismal Organism reproductive quality
49
How many types of shape are there
notched T-shaped Y-shaped branched unbranched antrose retrose curled curved wiggly squiggly round flat square oblong elliptical ovoid cuboid spherical egg-shaped rod-shaped heart-shaped hellip
How do we define them
How do we compare them
Shapes cannot be organized in a linear scale
Compare problem of classifying RNA structures
50
Standard case monadic qualitiesExamples
ndash E=kidney Q=hypertrophiedndash autodef a kidney which is hypertrophied
We assume that there is more contextual data (not shown)ndash eg genotype environment number of organisms
in study that showed phenotype
Interpretation (with the rest of the database record)ndash all fish in this experiment with a particular
genotype had a hypertrophied kidney at some point in time
51
Who should use PATO
Originallyndash model organism mutant phenotypes
But alsondash ontology-based evolutionary systematicsndash neuroscience BIRNndash clinical uses
bull OMIMbull clinical records (clinical manifestations)bull drug effects chemical effects
ndash to define terms in other ontologiesbull eg diploid cell invasive tumor engineered gene
condensed chromosome
- The Ontology of Experiments + PATO
- Plan
- EXPO
- Slide 4
- EXPO Formalisation of Science
- Slide 6
- Slide 7
- Slide 8
- Suggested Upper Merged Ontology
- SUMO top level
- Suggested Upper Merged Ontology
- SUMO Structure
- SUMO+Domain Ontology
- Slide 14
- Slide 15
- advantages of SUMO
- problems with SUMO as Upper-Level
- Slide 18
- Slide 19
- Slide 20
- Slide 21
- OBI
- Overview of the Ontology of Biomedical Investigations
- OBI neacutee FuGO
- Motivation for OBI
- Emerging FuGO Design Principles
- OBI Collaborating Communities
- Slide 28
- Slide 29
- FuGO - Top Level Universals
- Slide 31
- Slide 32
- Basic Formal Ontology
- Three dichotomies
- instance vs type
- BFO
- Slide 37
- Slide 38
- Unifying goal integration
- Some thoughts on the ontology itself
- Itrsquos all about the definitions
- Old PATO Entity ndash Attribute ndash Value Eye ndash Red ndash Dark
- What a quality is NOT
- Some examples of qualities
- Slide 45
- Qualities are dependent entities
- Slide 48
- How many types of shape are there
- Standard case monadic qualities
- Who should use PATO
-
49
How many types of shape are there
notched T-shaped Y-shaped branched unbranched antrose retrose curled curved wiggly squiggly round flat square oblong elliptical ovoid cuboid spherical egg-shaped rod-shaped heart-shaped hellip
How do we define them
How do we compare them
Shapes cannot be organized in a linear scale
Compare problem of classifying RNA structures
50
Standard case monadic qualitiesExamples
ndash E=kidney Q=hypertrophiedndash autodef a kidney which is hypertrophied
We assume that there is more contextual data (not shown)ndash eg genotype environment number of organisms
in study that showed phenotype
Interpretation (with the rest of the database record)ndash all fish in this experiment with a particular
genotype had a hypertrophied kidney at some point in time
51
Who should use PATO
Originallyndash model organism mutant phenotypes
But alsondash ontology-based evolutionary systematicsndash neuroscience BIRNndash clinical uses
bull OMIMbull clinical records (clinical manifestations)bull drug effects chemical effects
ndash to define terms in other ontologiesbull eg diploid cell invasive tumor engineered gene
condensed chromosome
- The Ontology of Experiments + PATO
- Plan
- EXPO
- Slide 4
- EXPO Formalisation of Science
- Slide 6
- Slide 7
- Slide 8
- Suggested Upper Merged Ontology
- SUMO top level
- Suggested Upper Merged Ontology
- SUMO Structure
- SUMO+Domain Ontology
- Slide 14
- Slide 15
- advantages of SUMO
- problems with SUMO as Upper-Level
- Slide 18
- Slide 19
- Slide 20
- Slide 21
- OBI
- Overview of the Ontology of Biomedical Investigations
- OBI neacutee FuGO
- Motivation for OBI
- Emerging FuGO Design Principles
- OBI Collaborating Communities
- Slide 28
- Slide 29
- FuGO - Top Level Universals
- Slide 31
- Slide 32
- Basic Formal Ontology
- Three dichotomies
- instance vs type
- BFO
- Slide 37
- Slide 38
- Unifying goal integration
- Some thoughts on the ontology itself
- Itrsquos all about the definitions
- Old PATO Entity ndash Attribute ndash Value Eye ndash Red ndash Dark
- What a quality is NOT
- Some examples of qualities
- Slide 45
- Qualities are dependent entities
- Slide 48
- How many types of shape are there
- Standard case monadic qualities
- Who should use PATO
-
50
Standard case monadic qualitiesExamples
ndash E=kidney Q=hypertrophiedndash autodef a kidney which is hypertrophied
We assume that there is more contextual data (not shown)ndash eg genotype environment number of organisms
in study that showed phenotype
Interpretation (with the rest of the database record)ndash all fish in this experiment with a particular
genotype had a hypertrophied kidney at some point in time
51
Who should use PATO
Originallyndash model organism mutant phenotypes
But alsondash ontology-based evolutionary systematicsndash neuroscience BIRNndash clinical uses
bull OMIMbull clinical records (clinical manifestations)bull drug effects chemical effects
ndash to define terms in other ontologiesbull eg diploid cell invasive tumor engineered gene
condensed chromosome
- The Ontology of Experiments + PATO
- Plan
- EXPO
- Slide 4
- EXPO Formalisation of Science
- Slide 6
- Slide 7
- Slide 8
- Suggested Upper Merged Ontology
- SUMO top level
- Suggested Upper Merged Ontology
- SUMO Structure
- SUMO+Domain Ontology
- Slide 14
- Slide 15
- advantages of SUMO
- problems with SUMO as Upper-Level
- Slide 18
- Slide 19
- Slide 20
- Slide 21
- OBI
- Overview of the Ontology of Biomedical Investigations
- OBI neacutee FuGO
- Motivation for OBI
- Emerging FuGO Design Principles
- OBI Collaborating Communities
- Slide 28
- Slide 29
- FuGO - Top Level Universals
- Slide 31
- Slide 32
- Basic Formal Ontology
- Three dichotomies
- instance vs type
- BFO
- Slide 37
- Slide 38
- Unifying goal integration
- Some thoughts on the ontology itself
- Itrsquos all about the definitions
- Old PATO Entity ndash Attribute ndash Value Eye ndash Red ndash Dark
- What a quality is NOT
- Some examples of qualities
- Slide 45
- Qualities are dependent entities
- Slide 48
- How many types of shape are there
- Standard case monadic qualities
- Who should use PATO
-
51
Who should use PATO
Originallyndash model organism mutant phenotypes
But alsondash ontology-based evolutionary systematicsndash neuroscience BIRNndash clinical uses
bull OMIMbull clinical records (clinical manifestations)bull drug effects chemical effects
ndash to define terms in other ontologiesbull eg diploid cell invasive tumor engineered gene
condensed chromosome
- The Ontology of Experiments + PATO
- Plan
- EXPO
- Slide 4
- EXPO Formalisation of Science
- Slide 6
- Slide 7
- Slide 8
- Suggested Upper Merged Ontology
- SUMO top level
- Suggested Upper Merged Ontology
- SUMO Structure
- SUMO+Domain Ontology
- Slide 14
- Slide 15
- advantages of SUMO
- problems with SUMO as Upper-Level
- Slide 18
- Slide 19
- Slide 20
- Slide 21
- OBI
- Overview of the Ontology of Biomedical Investigations
- OBI neacutee FuGO
- Motivation for OBI
- Emerging FuGO Design Principles
- OBI Collaborating Communities
- Slide 28
- Slide 29
- FuGO - Top Level Universals
- Slide 31
- Slide 32
- Basic Formal Ontology
- Three dichotomies
- instance vs type
- BFO
- Slide 37
- Slide 38
- Unifying goal integration
- Some thoughts on the ontology itself
- Itrsquos all about the definitions
- Old PATO Entity ndash Attribute ndash Value Eye ndash Red ndash Dark
- What a quality is NOT
- Some examples of qualities
- Slide 45
- Qualities are dependent entities
- Slide 48
- How many types of shape are there
- Standard case monadic qualities
- Who should use PATO
-