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Introduction to the Semantic Web
Semantic tecnologies – a quick overviewFulvio Corno
Politecnico di Torino
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Intellisemantic, Politecnico di Torino 202/07/2008
Semantic Web Web second generation
Web 3.0 “Conceptual structuring of the Web in an
explicit machine-readable way” (Tim Berners-Lee)
In other words…
…let the machine do most of the work!!!
http://www.w3.org/2001/sw/
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Intellisemantic, Politecnico di Torino 302/07/2008
‘Official’ introduction (1/2) The Semantic Web is a web of data. There is lots
of data we all use every day, and its not part of the web. I can see my bank statements on the web, and my photographs, and I can see my appointments in a calendar. But can I see my photos in a calendar to see what I was doing when I took them? Can I see bank statement lines in a calendar?
Why not? Because we don't have a web of data. Because data is controlled by applications, and each application keeps it to itself.
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Intellisemantic, Politecnico di Torino 402/07/2008
‘Official’ introduction (2/2) The Semantic Web is about two things. It is about
common formats for integration and combination of data drawn from diverse sources, where on the original Web mainly concentrated on the interchange of documents. It is also about language for recording how the data relates to real world objects. That allows a person, or a machine, to start off in one database, and then move through an unending set of databases which are connected not by wires but by being about the same thing.
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Intellisemantic, Politecnico di Torino 502/07/2008
Key principles The Semantic Web is the Web
Same base technologies, EvolutionaryDecentralized (incomplete, inconsistent)
Provide explicit statements regarding web resourcesAuthors, original information providers Intermediaries (humans and/or machines)
Information consumers determine consequences of the statementsDistributed ‘reasoning’
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Intellisemantic, Politecnico di Torino 602/07/2008
Technology stack (old: pre-2008)
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Intellisemantic, Politecnico di Torino 702/07/2008
Technology stack (current: 2008)
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Intellisemantic, Politecnico di Torino 802/07/2008
Comparison... current trends
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Intellisemantic, Politecnico di Torino 902/07/2008
Main technologies Resource Description Framework (RDF)
[2004] Gleaning Resource Descriptions from
Dialects of Languages (GRDDL) [2007] SPARQL Query Language for RDF [2008] Web Ontology Language (OWL) [2004]
http://www.w3.org/2001/sw/
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Intellisemantic, Politecnico di Torino 1002/07/2008
The real world...
Not yet...!
Notyet...!
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Intellisemantic, Politecnico di Torino 1102/07/2008
The real world...
Not yet...!
Notyet...!
Not always necessary...
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Intellisemantic, Politecnico di Torino 1202/07/2008
The real world...
Not yet...!
Notyet...!
Not always necessary...
Informationretrieval
Statistics
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Intellisemantic, Politecnico di Torino 1302/07/2008
Key concepts
Ontology
Annotation
Metadata
Knowledge
Search
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Metadata and Knowledge Representation
Semantic tecnologies – a quick overviewFulvio Corno
Politecnico di Torino
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Intellisemantic, Politecnico di Torino 203/07/2008
Key concepts
Ontology
Annotation
Metadata
Knowledge
Search
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Intellisemantic, Politecnico di Torino 303/07/2008
Metadata
Structured data about data Higher level information that describes
contentqualitystructureaccessibility…
of a specific data set
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Intellisemantic, Politecnico di Torino 403/07/2008
Problems Even the author, sometimes, has difficulty
in correctly classifying the contents Choice of “topics” may be done at different
levels, all of them “correct” Choice of “keywords” is afflicted by
synonyms and homonyms Typographical errors often appear in the
original text
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Intellisemantic, Politecnico di Torino 503/07/2008
Classification techniques Controlled vocabularies Taxonomies Thesauri Facets Ontologies Folksonomies
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Intellisemantic, Politecnico di Torino 603/07/2008
Controlled vocabulary A closed list of named subjects, which
can be used for classification Composed of terms [particular name for a
particular concept] (similar to keywords)
)
Terms are not conceptsA single term may be the name of one (or
more) concept(s)
m
A single concept may have multiple namesAmbiguity avoided by forbidding duplicate
terms
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Intellisemantic, Politecnico di Torino 703/07/2008
Controlled vocabulary Purpose:
to avoid authors defining meaningless terms, terms which are too broad, or terms which are too narrow
to prevent different authors from misspelling and choosing slightly different forms of the same term
The simplest form of controlled vocabulary is simply a list of terms and nothing more.
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Intellisemantic, Politecnico di Torino 803/07/2008
Problems solved Homograph
group of words that share the same spelling but have different meanings
Homonymgroup of words that share the same spelling or
pronunciation (or both) but have different meanings
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Intellisemantic, Politecnico di Torino 903/07/2008
Problems solved Synonym
different words with identical or at least similar meanings
Polysemythe capacity for a word to have multiple
meanings
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Intellisemantic, Politecnico di Torino 1003/07/2008
Example
http://www.iesr.ac.uk/profile/vocabs/index.html/#CtrldVocabsList
Information Environment Service Registry (IESR)
R
http://www.iesr.ac.uk/
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Intellisemantic, Politecnico di Torino 1103/07/2008
Taxonomy Subject-based classification that arranges
the terms in the controlled vocabulary into a hierarchyDating back to the work of Carl Linnæus in the
18th century on zoological and botanical classification and naming system for species
Benefit: they allow related terms to be grouped together and categorized in ways that make it easier to find the correct term to use for searching or to describe an object
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Intellisemantic, Politecnico di Torino 1203/07/2008
Taxonomy It is clear that "topic
maps" and "XTM" are related
Easier to classify documents
Easier to choose search keywords
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Intellisemantic, Politecnico di Torino 1303/07/2008
Taxonomies and metadata Metadata are stored
as usual with the resource
The “subject” will contain only controlled terms
Controlled terms belong to a hierarchy, shared by all papers
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Intellisemantic, Politecnico di Torino 1403/07/2008
Limitations A taxonomy may not express:
"XML Topic Maps" is synonymous with "XTM" difference between "XTM" and "topic maps". "topic navigation maps" is synonymous with "topic
maps", but should no longer be used\ relationship between topic maps and subject-based
classification, or the semantic web. relationship between XTM and XML and HyTM and
SGML. similarity between HyTM and XTM, and their
difference from TMQ
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Intellisemantic, Politecnico di Torino 1503/07/2008
Example
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Intellisemantic, Politecnico di Torino 1603/07/2008
Example
http://www.acm.org/class/1998/ccs98.html
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Intellisemantic, Politecnico di Torino 1703/07/2008
Thesaurus Extends taxonomies: subjects are
arranged in a hierarchy Other statements can be made about the
subjects Two ISO standards
ISO2788 for monolingual thesauriISO5964 for multilingual thesauri
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Intellisemantic, Politecnico di Torino 1803/07/2008
Thesaurus relationships BT – broader term
Refers to a term with wider or less specific meaning Some systems allow multiple BTs for one term, while
others do not Inverse property: NT - narrower term A taxonomy only uses BT and NT
SN – scope note String explaining its meaning within the thesaurus Useful when the precise meaning of the term is not
obvious from context.
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Intellisemantic, Politecnico di Torino 1903/07/2008
Thesaurus relationships
USEAnother term that is to be preferred instead of this
termImplies that the terms are synonymousInverse property: UF
TT – top termThe topmost ancestor of this termThe BT of the BT of the BT...
RT – related termA term that is related to this term, without being a
synonym of it or a broader/narrower term.
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Intellisemantic, Politecnico di Torino 2003/07/2008
Example
http://www.swinburne.edu.au/corporate/registrar/rms/keywords.htm
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Intellisemantic, Politecnico di Torino 2103/07/2008
Example Library of Congress
Subject Headings Since 1985 it
became a taxonomy
http://www.loc.gov/lexico/servlet/lexico/
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Intellisemantic, Politecnico di Torino 2203/07/2008
SKOS SKOS: Simple Knowledge Organization
Systemhttp://www.w3.org/2004/02/skos/ «SKOS provides a standard way to represent
knowledge organisation systems using the Resource Description Framework (RDF). Encoding this information in RDF allows it to be passed between computer applications in an interoperable way.»
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Intellisemantic, Politecnico di Torino 2303/07/2008
SKOS: example
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Intellisemantic, Politecnico di Torino 2403/07/2008
Facets Proposed by S.R. Ranganathan in the 1930s Identifies a number of facets into which the
terms are divided. Facets can be thought of as different axes along
which documents can be classified Each facet contains a number of terms
Usually with at thesaurus-like organization A term is only allowed to belong to a single facet
A document is classified by picking one term from each facet to describe the document along all the different axes
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Intellisemantic, Politecnico di Torino 2503/07/2008
Advantages Multi-dimensionality Persistence Scalability Flexibility
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Intellisemantic, Politecnico di Torino 2603/07/2008
Examplehttp://flamenco.berkeley.edu/
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Intellisemantic, Politecnico di Torino 2703/07/2008
Examplehttp://intellisemantic.myvnc.com:8080/IntelliFacet/
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Intellisemantic, Politecnico di Torino 2803/07/2008
Ontology Model for describing the world that
consists of a set of types, properties, and relationships
Extends the other subject-based classification approachesHas open vocabulariesHas open relationship types
Not just BT/NT + USE/UF
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Intellisemantic, Politecnico di Torino 2903/07/2008
Ontology structure Concepts Relationships
Is-aOther
Instances
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Intellisemantic, Politecnico di Torino 3003/07/2008
Examplehttp://onto.stanford.edu:8080/wino/index.jsp
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Intellisemantic, Politecnico di Torino 3103/07/2008
Folksonomy Internet-mediated social environments Collaboratively generated, open-ended
labeling system that enables Internet users to categorize content such as Web pages, online photographs, and Web links
Users can discover who created a given folksonomy tag, and see the other tags that this person createdreward: better user’s capacity to find related
content
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Intellisemantic, Politecnico di Torino 3203/07/2008
Example (wikipedia)
�
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Intellisemantic, Politecnico di Torino 3303/07/2008
Example (flickr - del.icio.us)
E
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Intellisemantic, Politecnico di Torino 3403/07/2008
Referenceshttp://www.controlledvocabulary.com/links.htmlhttp://en.wikipedia.org/wiki/Controlled_vocabularyhttp://www.ontopia.net/topicmaps/materials/tm-vs-
thesauri.html http://www.w3.org/2004/02/skos/ http://en.wikipedia.org/wiki/SKOS
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Ontologies
Semantic tecnologies – a quick overviewFulvio Corno
Politecnico di Torino
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Intellisemantic, Politecnico di Torino 203/07/2008
Key concepts
Ontology
Annotation
Metadata
Knowledge
Search
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Intellisemantic, Politecnico di Torino 303/07/2008
What are the problems? People, Organizations, Software Systems
must communicateAmong themselvesTo the others
ObstaclesDifferent needsDifferent backgroundDifferent viewpointsDifferent assumptions
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Intellisemantic, Politecnico di Torino 403/07/2008
How to solve them? resolve terminological confusion resolve conceptual confusion come to a shared understanding A shared understanding serves for:
providing a unifying framework for different viewpoints
providing the basis for communication between different people from different contexts
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Intellisemantic, Politecnico di Torino 503/07/2008
Ontologies: summary
An ontology is an explicit description of a domainconceptsproperties and attributes of conceptsconstraints on properties and attributes individuals (often, but not always)
An ontology defines a common vocabularya shared understanding
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Intellisemantic, Politecnico di Torino 603/07/2008
Example
chair
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Intellisemantic, Politecnico di Torino 703/07/2008
Example
●A piece of furniture consisting of a seat, legs, back, and often arms, designed to accommodate one person.●A seat of office, authority, or dignity, such as that of a bishop.
●An office or position of authority, such as a professorship.●A person who holds an office or a position of authority, such as one who presides over a meeting or administers a department of instruction at a college; a chairperson.
●The position of a player in an orchestra.●Slang. The electric chair.●A seat carried about on poles; a sedan chair.●Any of several devices that serve to support or secure, such as a metal block that supports and holds railroad track in position.
chair
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Intellisemantic, Politecnico di Torino 803/07/2008
Example
A piece of furniture consisting of a seat, legs, back, and often arms, designed to accommodate one person.
chair
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Intellisemantic, Politecnico di Torino 903/07/2008
Example
chair seat stool bench
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Intellisemantic, Politecnico di Torino 1003/07/2008
Example
Something I can sit on
chair seat stool bench
Something I can sit on
???
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Intellisemantic, Politecnico di Torino 1103/07/2008
chair seat stool bench
Something I can sit on
“sittable”
Example
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Intellisemantic, Politecnico di Torino 1203/07/2008
chair seat stool bench
table
Example
Something I can sit on
“sittable”
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Intellisemantic, Politecnico di Torino 1303/07/2008
Example
Something I can sit on
chair seat stool bench
“for_sitting”
table
“sittable”
Something designed for sitting
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Intellisemantic, Politecnico di Torino 1403/07/2008
Ontology structure
chair seat stool bench
“for_sitting”
table
“sittable”
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Intellisemantic, Politecnico di Torino 1503/07/2008
Ingredients
Conceptsshorthand name (internal use)synthetic title (to be displayed)definition (real unambiguous shared definition)
Relationships among concepts is_aother
Annotations
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Intellisemantic, Politecnico di Torino 1603/07/2008
Relationships
chair seat stool bench
“for_sitting”
table
“sittable”
is_a is_a is_ais_a
is_a
is_a
roommaterial
wood
is_a
classroom
dining room
is_ais_a
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Intellisemantic, Politecnico di Torino 1703/07/2008
Relationships
chair seat stool bench
“for_sitting”
table
“sittable”
is_a is_a is_ais_a
is_a
is_a
roommaterial
wood
is_a
classroom
dining room
is_ais_a
made_of
furnished
made_of
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Intellisemantic, Politecnico di Torino 1803/07/2008
Ontology building blocks Ontologies generally describe:
Individuals the basic or "ground level" objects
Classes sets, collections, or types of objects
Attributes properties, features, characteristics, or parameters
that objects can have and shareRelationships
ways that objects can be related to one another
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Intellisemantic, Politecnico di Torino 1903/07/2008
Ontology languages
XML
XOL SHOE OML RDF(S)
OIL
OWL
DAML+OIL
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Intellisemantic, Politecnico di Torino 2003/07/2008
RDF Resource Description Framework
Resource = URI (retrievable, or not) RDF is structured in statements A statement is a triple:
Subject predicate object Subject: a resource Predicate: a verb / property / relationship Object: a resource, or a literal string
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Intellisemantic, Politecnico di Torino 2103/07/2008
RDF examples http://elite.polito.it/people#FulvioCorno
http://purl.org/vocab/relationship/employedBy http://www.polito.it
http://elite.polito.it/people#FulvioCorno hasProfession http://reliant.teknowledge.com/DAML/Mid-level-ontology.owl#Professor
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Intellisemantic, Politecnico di Torino 2203/07/2008
RDF in XML
<rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:dc="http://purl.org/dc/elements/1.1/"> <rdf:Description rdf:about="http://en.wikipedia.org/wiki/Tony_Benn"> <dc:title>Tony Benn</dc:title> <dc:publisher>Wikipedia</dc:publisher> </rdf:Description></rdf:RDF>
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Intellisemantic, Politecnico di Torino 2303/07/2008
RDF from multiple dictionaries<rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:foaf="http://xmlns.com/foaf/0.1/" xmlns:dc="http://purl.org/dc/elements/1.1/"> <rdf:Description rdf:about="http://en.wikipedia.org/wiki/Tony_Benn"> <dc:title>Tony Benn</dc:title> <dc:publisher>Wikipedia</dc:publisher> <foaf:primaryTopic> <foaf:Person> <foaf:name>Tony Benn</foaf:name> </foaf:Person> </foaf:primaryTopic> </rdf:Description></rdf:RDF>
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Intellisemantic, Politecnico di Torino 2403/07/2008
RDF and RDF schema
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Intellisemantic, Politecnico di Torino 2503/07/2008
Formal ontologies A formal ontology
is defined using a language with a formal semantics well defined meaning of the language constructs well known rules to combine them
is bound to a given logic theory first-order logic description logic ...
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Intellisemantic, Politecnico di Torino 2603/07/2008
OWL - Introduction 4th level on the semantic web cake built on top of
XMLRDF/S
Three versionsLiteDL (maps to Description Logic)Full (not fully tractable)
Serializable as XML
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Intellisemantic, Politecnico di Torino 2703/07/2008
OWL: Ontology Web Language
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Intellisemantic, Politecnico di Torino 2803/07/2008
OWL-DL Based on Description Logic Well defined formal semantics
well defined rules to treat sentence meaningwell defined assumptions on the world being
modeled Well known reasoning/inferencing
algorithmstractable, conclusions can be derived in finite
time Widely available reasoning systems
no need to re-invent the wheel
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Intellisemantic, Politecnico di Torino 2903/07/2008
Building blocks in OWL Ontology declaration (XML syntax)
Ontology metadata (information about the ontology)
<rdf:RDF xmlns:owl =http://www.w3.org/2002/07/owl#"
xmlns:rdf ="http://www.w3.org/1999/02/22-rdf-syntax-ns#"
xmlns:rdfs="http://www.w3.org/2000/01/rdf-schema#"
xmlns:xsd ="http://www.w3.org/2001/XMLSchema#">
<owl:Ontology rdf:about=""><rdfs:comment>An example OWL ontology</rdfs:comment><owl:priorVersionrdf:resource="http://www.mydomain.org/uni-ns-old"/><owl:importsrdf:resource="http://www.mydomain.org/persons"/><rdfs:label>University Ontology</rdfs:label>
</owl:Ontology>
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Intellisemantic, Politecnico di Torino 3003/07/2008
Classes Every class is a descendant of
owl:Thing Are defined using
owl:Class
Equivalenceowl:equivalentClass
<owl:Class rdf:ID="Vehicle"/>
<owl:Class rdf:ID="Car">
<owl:equivalentClass rdf:resource="#Automobile"/>
</owl:Class>
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Intellisemantic, Politecnico di Torino 3103/07/2008
Subsumption Provided by
owl:subClassOf
<owl:Class rdf:ID="2-Wheel-Drive">
<rdfs:subClassOf rdf:resource="#Car"/>
</owl:Class>
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Intellisemantic, Politecnico di Torino 3203/07/2008
Partitions Disjoint partition
owl:disjointWith
<owl:Class rdf:about="#2-Wheel-Drive">
<owl:disjointWithrdf:resource="#4-Wheel-Drive"/>
</owl:Class>
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Intellisemantic, Politecnico di Torino 3303/07/2008
Partitions Exhaustive partition
owl:oneOf
<owl:Class rdf:ID="Car">
<owl:oneOf rdf:parseType="Collection">
<owl:Thing rdf:about="#2-Wheel-Drive"/>
<owl:Thing rdf:about="#4-Wheel-Drive"/>
</owl:oneOf>
</owl:Class>
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Intellisemantic, Politecnico di Torino 3403/07/2008
Attributes Known as “properties” Subdivided in
Datatype properties Attributes that specify a class features by means of
data (XSD datatype) phone, title, age
Object properties Attributes that define relationships between classes
(Relations) isTaughtBy(Class(course), Class(professor))
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Intellisemantic, Politecnico di Torino 3503/07/2008
Attributes - datatypeProperties Allow to describe a specific aspect of a
conceptBased on XSD data typesThe range specifies the data typeThe domain specifies the class to which the
property is referred
<owl:DatatypeProperty rdf:ID="age">
<rdfs:domain rdf:resource="#Person"/>
<rdfs:range rdf:resource="http://www.w3.org/2001/XMLSchema#nonNegativeInteger"/>
</owl:DatatypeProperty>
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Intellisemantic, Politecnico di Torino 3603/07/2008
Relationships Directed (from one concept to another, no
viceversa) Defined through object properties
domain the class(es) from which the relation departs
range the relation destination(s)
Subsumption between relationships is possible
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Intellisemantic, Politecnico di Torino 3703/07/2008
Relationships Example
<owl:ObjectProperty rdf:ID="isTaughtBy">
<rdfs:domain rdf:resource="#course"/>
<rdfs:range rdf:resource="#academicStaffMember"/>
<rdfs:subPropertyOf rdf:resource="#involves"/>
</owl:ObjectProperty>
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Intellisemantic, Politecnico di Torino 3803/07/2008
Instances (Individuals) Defined by means of
rdf:Description + rdf:Type No unique name assumption
if two instances have a different name or ID this does not imply that they are different individuals.
<academicStaffMember rdf:ID="949352"><uni:age rdf:datatype="&xsd;integer">
39</uni:age>
</academicStaffMember>
<rdf:Description rdf:ID="949353"><rdf:type rdf:resource="#academicStaffMember"/></rdf:Description>
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Intellisemantic, Politecnico di Torino 3903/07/2008
Advanced constructs OWL supports several advanced constructs
to define classes and relationships Intensional definition of classes
by defining constraints on attribute values (either object or datatype properties)
<owl:Class rdf:about="#academicStaffMember"><rdfs:subClassOf>
<owl:Restriction><owl:onProperty rdf:resource="#teaches"/><owl:someValuesFrom
rdf:resource="#undergraduateCourse"/></owl:Restriction>
</rdfs:subClassOf></owl:Class>
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Intellisemantic, Politecnico di Torino 4003/07/2008
Advanced constructs Cardinality
Used to fix the number of instances that can be related
example: A department should have at least 10 members
<owl:Class rdf:about="#department"> <rdfs:subClassOf>
<owl:Restriction><owl:onProperty rdf:resource="#hasMember"/><owl:minCardinality
rdf:datatype="&xsd;nonNegativeInteger">10
</owl:minCardinality></owl:Restriction>
</rdfs:subClassOf></owl:Class>
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Intellisemantic, Politecnico di Torino 4103/07/2008
Special properties (1/2) owl:TransitiveProperty
defines a transitive property, such as “has better grade than”, “is taller than”, or “is ancestor of”.
owl:SymmetricProperty defines a symmetric property, such as “has
same grade as” or “is sibling of”. owl:FunctionalProperty
defines a property that has at most one value for each object, such as “age”, “height”, or “directSupervisor”.
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Intellisemantic, Politecnico di Torino 4203/07/2008
Special properties (2/2) owl:InverseFunctionalProperty
defines a property for which two different objects cannot have the same value
example the property “isTheSocialSecurityNumberFor” a social security number is assigned to one person
only.
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OWL class constructors
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OWL axioms
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Intellisemantic, Politecnico di Torino 4503/07/2008
Open questions... Reasoning is only feasible for OWL-DL
limitations vocabulary partition
a resource can only be a class, an object property, a datatype property (a class cannot be at same time an individual)
explicit typing partitioning must be stated explicitly
no transitive cardinality restrictions transitive properties cannot have cardinality restrictions
Some semantics is still missinge.g. how to define what a given relation
means?
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Intellisemantic, Politecnico di Torino 4603/07/2008
SWRL (quick glance) SWRL
Semantic Web Rule Language Can be used to define new relationships
(thus provides their operational semantics) Builds on top of RDF Example:
Base predicates Father(?x,?y) Mother(?x,?z)
New relations (defined through SWRL) Father(?x,?y)→Parent(?x,?y) Mother(?x,?z)→Parent(?x,?y)
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Intellisemantic, Politecnico di Torino 4703/07/2008
SWRL (quick glance) Example 2
DomoMLPlus:Room(?x) ^ DomoMLPlus:hasWall(?x, ?z) ^ DomoMLPlus:hasWallOpening(?z, ?y)^ DomoMLPlus:Window(?y)→ DomoMLPlus:hasWindows(?x, true)
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Intellisemantic, Politecnico di Torino 4803/07/2008
No ontology, no semantics Reuse of existing taxonomies as
ontologies Publicly available ontologies
Horizontal ontologies (SUMO, MILO, WordNet, ...)
Vertical ontologies (domain-specific)
Semi-automatic ontology learning from resources
Manual development / enrichment