eco r european centre for ontological research ontology for medical emergency related resource...

ECOREuropean Centre forOntological Research

Ontology forMedical Emergency related

Resource Location

Werner CeustersEuropean Centre for Ontological Research

Universität des Saarlandes

Saarbrücken, Germany


Presentation overview

• Professional background

• Ontology and terminology

• Concepts as the source of all evil

• Realist ontology

• Setting the scene for an ontology of emergency medicine


Short personal history

1959 - ...1977

1989

1992

1998

2002

2004


European Centre forOntological Research

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Externalmembers

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Status April 8, 2005


European Centre forOntological Research

Directors Member representatives

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Management Board



Institute for Formal Ontologyand Medical Information Science

• an interdisciplinary research group – Philosophy, – Computer and Information Science, – Logic, – Medicine, – Medical Informatics.

• a center of theoretically grounded research in both formal and applied ontology.

• Main goal: to develop a formal ontology that will be applied and tested in the domain of medical and biomedical information science.


IFOMIS competences•Logics X X X

•Informatics X X

•Spatio-temporal reasoning X

•Medicine X X X

•Knowledge engineering X

•Formal Ontology / metaphysics X X X X X

•Mathematics X X

•Qualitative spatial reasoning X X

•Ontological engineering X X

•History of philosophy X

•Philosophy of science X

•Linguistics X



“Ontology”


If, later, you can remember just one thing of this presentation, then make

sure it is this one:

If you use the word “ontology”, ALWAYS

be specific about what you mean by it.


Tom Gruber’s view

• In the context of knowledge sharing, I use the term ontology to mean a specification of a conceptualization. That is, an ontology is a description (like a formal specification of a program) of the concepts and relationships that can exist for an agent or a community of agents. This definition is consistent with the usage of ontology as set-of-concept-definitions, but more general. And it is certainly a different sense of the word than its use in philosophy.

• The word "ontology" seems to generate a lot of controversy in discussions about AI. It has a long history in philosophy, in which it refers to the subject of existence. It is also often confused with epistemology, which is about knowledge and knowing.

ECOREuropean Centre forOntological Research The O-word in science

N. Guarino, P. Giaretta, "Ontologies and Knowledge Bases: Towards a Terminological Clarification". In Towards Very Large Knowledge Bases: Knowledge Building and Knowledge Sharing, N. Mars (ed.), pp 25-32. IOS Press, Amsterdam, 1995.

ECOREuropean Centre forOntological Research The O-word in buzz-speak

• “An ontology is a classification methodology for formalizing a subject's knowledge or belief system in a structured way. Dictionaries and encyclopedias are examples of ontologies.”

(X1)

• “A terminology (or classification) is a kind of ontology by definition and it should preserve (and "understand") the relationships between the 1,000s of terms in it or else it would become a mere dictionary (or at best a thesaurus).”

(X2)

• “Ontologies are Web pages that contain a mystical unifying force that gives differing labels common meaning.”

(X3)


Today’s biggest problem:a confusion between

“terminology” and “ontology”

• The conditions to be agreed upon when to use a certain term to denote an entity, are often different from the conditions which make an entity what it is.– Trees would still be different from rabbits even if there

were no humans to agree on what names we should use to refer to them

• “ontos” means “being”. The link with reality tends to be forgotten: one concentrates on the models instead of on the reality.


Use Case: Semantic Discovery of Community of Practice

COCOON Working Draft 16 Decembre 2004

2.5.1 Ontologies. First of all we need : a set of ontologies that provide the terminology used later. We introduce:• an advice service terminology for specifying the action of a

general practitioner asking a CoP for an advices, • a set of domain terminologies for specifying the case the

general practitioner is asking an advice for (in the mock-ups presented in sections sec:mock-up we decide to use a small breast cancer ontology),

• a date and time terminology for specifying days of the week, hours of the day and intervals required for arranging a meeting, and

• a terminology of the available communication channels used during the virtual meeting that will take place after the arrangement.


Terminology

• A theory concerned with those aspects of the nature and the functions of language which permit the efficient representation and transmission of items of knowledge (J. Sager)

• Precise and appropriate terminologies provide important facilities for human communication (J. Gamper)

ECOREuropean Centre forOntological Research Ontology

What it means if we use the wordA proposal put forward by the SI roadmap

pannel

• An ontology is a representation of some pre-existing domain of reality which

– (1) reflects the properties of the objects within its domain in such a way that there obtains a systematic correlation between reality and the representation itself,

– (2) is intelligible to a domain expert

– (3) is formalized in a way that allows it to support automatic information processing


Copyright 2001, United Feature Syndicate Inc.

Reality: not just a matter of view


A division of labour

• Terminology:– Communication amongst humans– Communication between human and machine

• Ontology:– Representation inside a machine of reality as it

exists outside the machine• a representation is not a model or a simplification;

‘cats’ is not a simplification of cats

– Communication amongst machines– Interpretation by machines


Current “state of the art” inbiomedical informatics

• A pervasive bias towards “concepts”– Content wise:

• Work based on ISO/TC37 that advocates the Ogden-Richards theory of meaning

• Corresponds with a linguistic reading of “concept”

– Architecture wise: • In Europe: work based on CEN/TC251 WG1 & WG2

that follow ISO/TC37• In the US: HL7, inspired by Speech Act Theory• “Concepts” used as elements of information models,

hence mixing a linguistic and engineering reading.


“Ontology”

An ontology defines the terms used to describe and represent an area of knowledge, and are used by people, databases, and applications that need to share domain information (a domain is a specific subject area, such as health or medicine).

OWL Web Ontology Language; Use Cases and RequirementsW3C Recommendation 10 February 2004

http://www.w3.org/TR/webont-req/

e-Health - making healthcare better for European citizens: An action plan for a European e-Health Area

COM (2004) 356 final, 30.4.2004, p17


• Ontologies need to specify descriptions for the following kinds of concepts:– Classes (general things) in the many domains

of interest – The relationships that can exist among things – The properties (or attributes) those things may

have

OWL Web Ontology Language; Use Cases and RequirementsW3C Recommendation 10 February 2004

http://www.w3.org/TR/webont-req/

“Ontology”


Semantic Interoperability

• Semantic interoperability is the ability for information shared by systems to be understood at the level of formally defined domain concepts so that the information is computer processable by the receiving system

– Text used in the CEC documents– Taken over by Artemis

ECOREuropean Centre forOntological Research ‘Concepts’ are the bad guys:

‘Concept’ used in ‘ontology’is used for different things

• meaning shared in common by synonymous terms

• idea shared in common in the minds of those who use these terms

• unit of knowledge describing meanings

• universal, feature or property shared in common by entities in the world


What concepts allow you to do

• Horse ISA mammal• One-horned mammal ISA mammal• Rhinoceros ISA one-horned mammal• Unicorn ISA one-horned mammal

• Small horse ISA horse• Horse in the zoo of Antwerp ISA horse• Horse that won the St.Gallen Steeple Chase in 2005 ISA

horse

Facts and fictions run together

Statements disguised as concepts


Origine: the semantic triangle• In Information Science:

– “An ontology is a description (like a formal specification of a program) of the concepts and relationships that can exist for an agent or a community of agents.”

• In Philosophy:– “Ontology is the science of

what is, of the kinds and structures of objects, properties, events, processes and relations in every area of reality.”

concept

term referent

ECOREuropean Centre forOntological Research The price you pay if you

gofor concepts ... (just one example)

UMLS Semantic Network– What does A relation B means ?– Normally: for all a’s that are A’s, there is some b that is

a B, such that the relation holds from a to b– Very relaxed: for some a’s there might be a b such that

a relation b– But even that doesn’t work for the relationship prevents


Ok, some more. It’s just too funny...

• UMLS-SN: – Bacterium causes Experimental model of disease– Educational activity associated with pathologic function

• HL7: Individual Allele is_a Act of Observation

• GO: Menopause part_of Death

• GALEN:– Female Pelvic Cavity Contains Uterus (this is ok, but compare ...)

– Vomitus Contains Carrot– Speech Contains Verbal Statement


‘Well, that’s because they don’t

use description logics or OWL’

SNOMED-RT (2000)

SNOMED-CT (2003)

DL don’t guarantee you to get parthood right !

You really think so ?


F-DL

(Frankenstein’s DL)

ECOREuropean Centre forOntological Research Our way:

Realist Ontology

• Central are the “particulars” (p)– Me, you, my heart, that patient’s fracture, that car

accident (which caused his fracture),…– ‘Referent tracking’

• Particulars instanciate classes (c) distinguished on the basis of ontological properties:– Essence, dependency, identity, relationship with time, …– Some classes are “universals” (u)

• Define relationships axiomatically at four levels:– p – p, c – c, p – c, c – p


BFO continuants


Kinds of relations

• <instance, instance>: – my heart part_of me

• <instance, class>: – me instance_of human being

• <class, instance>: – president of the US empowered_by US

constitution (?)

• <class, class>: – gene expression has_agent RNA polymerase


Parthood as a Relation between Instances

• Introduced as primitive:– p part_of p1

• Illustrated in assertions such as: – My heart part_of Werner Ceusters

• Properties:– reflexivity: for all p, p part_of p,– anti-symmetry: for all p, p1, if p part_of p1

and p1 part_of p then p and p1 are identical,– transitivity: for all p, p1, p2, if p part_of p1 and

p1 part_of p2, then p part_of p2.


Parthood as a Relation between Classes

• For continuants: (‘heart’, ‘person’)– C part_of C1 =def. for all c, t, if c instance_of

C at t then there is some c1 such that c1 instance_of C1 at t and c part_of c1 at t.

• For processes: (‘menopauze’, ‘aging’)– P part_of P1 =def. for all p, if p instance_of P,

then there is some p1 such that: p1 instance_of P1 and p part_of p1.

These definitions tell you ONLY something about C’s and P’s, but nothing about C1’s and P1’s !!!


Possible variants

• R1(A, B) =: x (Inst(x, A) y(Inst(y, B) & Rxy)) – every A stands in relation R to some B

• R2(A, B) =: y (Inst(y, B) x(Inst(x, A) & Rxy))– for each B there is some A that stands in relation R

to it

• R12(A, B) =: R1(A, B) & R2(A, B)– every A stands in relation R to some B and for each

B there is some A that stands in relation R to itDonnelly and Bittner, 2005


Properties of relations among individuals vs. properties of relations among classes

Among Individuals

Among Classes

R is... R1 must also

be...?

R2 must also

be...?

R12 must also

be...?

Reflexive Yes Yes Yes

Irreflexive No No No

Symmetric No No Yes

Asymmetric No No No

Antisymmetric No No No

Transitive Yes Yes Yes

Donnelly and Bittner, 2005


GALEN assertions using isDivisionOF and hasDivision

GALEN’s isDivisionOf assertion BIT+Clrelation

GALEN’s hasDivision BIT+Clrelation

Female Pelvic Cavity isDivisionOf Pelvic Part of Trunk

PP1 none

Prostate Gland isDivisionOf Genito-Urinary System

PP1 none

none Pelvic Part of Trunk hasDivision Hair

(PP-1)1

LeftHeartVentricle isDivisionOf Heart

PP12 Heart hasDivision LeftHeartVentricle

(PP-1)12

Prostate Gland isDivisionOf Male Genito-Urinary System

PP12 Male Genito-Urinary System hasDivision Prostate Gland

(PP-1)12

Urinary Bladder isDivisionOf Genito-Urinary System

PP12 none

Pericardium isDivisionOf Heart none Heart hasDivision Pericardium none

Donnelly and Bittner, 2005

ECOREuropean Centre forOntological Research Realist Ontology is alive

• The gossip:– We are holding biomedical ontology in a strangle hold

• The success stories (some recent examples):– Contributing to OBO ontologies requires adherence to the

relations defined in Relations in Biomedical Ontologies, forthcoming in Genome Biology

– Foundational Medical Anatomy (FMA) completely reworked, and basis for forthcoming CEN standard

– Previous IFOMIS collaborator hired by NLM to work on revision of Semantic Network

– Barry Smith appointed by De Soto (Institute for Liberty and Democracy), funded by US Agency for International Development, to establish the philosophical underpinnings of property right.


Towards an ontology formedical emergencies

Preliminary thoughts to start discussion


DICOEMS ontology use case

• Main goal:– locating the suitable resources and experts that can treat the specific

medical emergency case that the paramedics face in the ambulance.

• Scenario:– expert in Emergency Center enters search terms in natural language

based on input from paramedics on site and telemedicine equipment– NLP processing of input to retain relevant words and their synonyms

(WordNet processing).– These words are used to retrieve concepts, terms and relations from

an ‘ontology’ about cardiovascular diseases– Ontology entries are linked to available resources (hospitals,

departments and experts)– Search output: in XML, concepts + codes that will form the input for

the Resources mapping module.

ECOREuropean Centre forOntological Research What are the particulars ?

• The particulars of the ‘current case’– The victim

• The disorder(s) that constitute(s) the emergency case• His personal history• ...

– Time and place– The on site team

• It’s experience, skills, ...• ...

– On site equipment– The emergency centre specialist– ...

• The particulars of previous cases– Same as above, plus ...... outcomes

Referent tracking

ECOREuropean Centre forOntological Research Useful source for inspiration:

Emergency Data Sets Framework

ISO TC 215/SC N Date: 2003-05-06 ISO/PDTR 1ISO TC 215/SC /WG 1 Secretariat: ANSI

An approach and tool to describe the world of data sets within thedomain of health informatics.


Emergency Medical ServiceClinical & Interventional

• Chief complaint• Cause of injury• Provider's impressions• Pre-existing condition• Signs and symptoms• Injury description• Injury intent• Safety equipment / protection

(seatbelt)• Factors affecting EMS delivery of

care• Alcohol/drug use• Trauma Score• Procedure or treatment• Medication name• Treatment authorization• Destination

– Hospital case number– Physician/Nurse accepting patient– Time dispatched

• CPR– Vital signs– Time of first CPR– Provider of first CPR– Time CPR discontinued– Time of witnessed cardiac arrest– Witness to cardiac arrest– Time of first defibrillatory shock– Return of spontaneous circulation– Pulse, heart rate, rhythm– Respiratory rate– Respiratory effort– Blood pressure– Skin perfusion

• Mental status– Glasgow eye-opening component– Glasgow verbal component– Glasgow motor component– Glasgow Coma– Psychological score (CRAMS)

ECOREuropean Centre forOntological Research The division of labour

• Ontology:– Identification of relevant particulars and classes– Identification and definition of relevant relationships at

all levels– Adequate representation

• Terminology:– Description of particulars, classes and relationships

using natural language (terms)– Links to literature, databases, resource descriptions

Machine – machine interfaces

Man – machine interfaces

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