1. Ontology & OWL Semantic Web - Fall 2005 Computer Engineering Department Sharif University of Technology

2. Outline  Introduction & Definitions  Ontology Languages  OWL

3. Where does it come from?  ontology n. 1692; lat. phil. onto- “being” + -logia “study of”  Philosophy The study of what is, what has to be true for something to exist, the kinds of things that can exist  AI and computer science Co-opted the term. Something exists if it can be represented, described, defined (in a formal, hence, machine-interpretable way).

4. Ontologies

5. Ontologies (contd.)  Ontologies are about vocabularies and their meanings, with explicit, expressive, and well- defined semantics, possibly machine- interpretable.  “Ontology is a formal specification of a conceptualization.” Gruber, 1993  Main elements of an ontology: Concepts Relationships  Hierarchical  Logical Properties Instances (individuals)

6. A Definition  Informal Terms  from a specific domain  uniquely defined, usually via natural language definitions May contain additional semantics in the form of informal relations machine-processing is difficult Examples  Controlled vocabulary  Glossary  Thesaurus

7. A Definition  Formal Domain-specific vocabulary Well-defined semantic structure  Classes/concepts/types  E.g., a class { Publication } represents all publications  E.g., a class { Publication } can have subclasses { Newspaper }, { Journal }  Instances/individuals/objects  E.g., the newspaper Le Monde is an instance of the class { Newspaper }  Properties/roles/slots  Data  E.g., the class { Publication } and its subclasses { Newspaper }, { Journal } have a data property { numberOfPages }  Object  E.g., the class { Publication } and its subclasses { Newspaper }, { Journal } have an object property { publishes } Is machine-processable

8. Ontologies in the Semantic Web  Provide shared data structures to exchange information between agents  Can be explicitly used as annotations in web sites  Can be used for knowledge-based services using other web resources  Can help to structure knowledge to build domain models (for other purposes)

9. Meaning is in Connections W i n e i s m a d e f r o m G r a p e Wine is made from Grape

10. For machines...      XML document     We are defining the structure of document by XML The meaning of the document is not defined. Machines cannot understand it. but now the meaning of the structure is not defined.

11.     Ontology gives the meaning... Document Ontology Natural Language

12. Why develop ontologies?  To share knowledge E.g., using an ontology for integrating terminologies  To reuse domain knowledge E.g., geography ontology  To make domain assumptions explicit Facilitate knowledge management Enable new users to learn about the domain  To distinguish domain knowledge from operational knowledge e.g., biblio metadata

13. What they are good for  Informal Controlled vocabulary  Beginnings of interoperability Upper-level structures for extending further  E.g., AGRIS/CARIS categorization Browsing support  E.g., IRS information search Search  Limited query expansion disambiguation  e.g., “Jordan” as a name of Basket-ball player and name of a country

14. What they are good for  Formal Search  Concept-based query  User uses own words, language  Related terms  Intelligent query expansion: “fishing vessels in China” expands to “fishing vessels in Asia” Consistency checking  e.g., “Goods” has a property called “price” that has a value restriction of number Interoperability support  Terms defined in expressive ontologies allow for mapping precisely how one term relates to another

15. Ontology Languages  Graphical notations Semantic networks Topic maps UML RDF  Logic based Description Logics (e.g., OIL, DAML+OIL, OWL) Rules (e.g., RuleML, LP/Prolog) First Order Logic

16. Ontology Languages RDF(S) (Resource Description Framework (Schema)) OIL (Ontology Interchange Language) DAML+OIL (DARPA Agent Markup Language + OIL) OWL (Ontology Web Language) XOL (XML-based Ontology Exchange Language) SHOE (Simple HTML Ontology Extension) OML (Ontology Markup Language)

17.  Many languages use object oriented model: Objects/Instances/Individuals  Elements of the domain of discourse  Equivalent to constants in FOL Types/Classes/Concepts  Sets of objects sharing certain characteristics  Equivalent to unary predicates in FOL and Concepts in DL Relations/Properties/Roles  Sets of pairs (tuples) of objects  Equivalent to binary predicates in FOL and Roles in DL Object oriented model

18. OWL (Ontology Web Language)  OWL is now a W3C Recommendation  The purpose of OWL is identical to RDFS i.e. to provide an XML vocabulary to define classes, properties and their relationships. RDFS enables us to express very rudimentary relationships and has limited inferencing capability. OWL enables us to express much richer relationships, thus yielding a much enhanced inferencing capability.  The benefit of OWL is that it facilitates a much greater degree of inference than you get with RDF Schema.

19. Origins of OWL RDF DAML+OIL DARPA Agent Markup Language A W3C Recommendation OIL OWL All influenced by RDF Ontology Inference Layer EU/NSF Joint Ad hoc Committee DAML OWL Lite OWL DL OWL Full

20. OWL  OWL and RDF Schema enable rich machine-processable semantics XML/DTD/XML Schemas RDF Schema OWL Semantics Syntax RDFS OWL

21. Why Build on RDF  Provides basic ontological primitives Classes and relations (properties) Class (and property) hierarchy  Can exploit existing RDF infrastructure  Provides mechanism for using ontologies RDF triples assert facts about resources Use vocabulary from DAML+OIL ontologies

22. OWL Design Goals  Shared ontologies  Ontology evolution  Ontology interoperability  Inconsistency detection  Expressivity vs. scalability  Ease of use  Compatibility with other standards  Internationalization

23. Full: Very expressive, no computation guarantees DL (Description Logic): Maximum expressiveness, computationally complete Lite: Simple classification hierarchy with simple constraints. Versions of OWL  Depending on the intended usage, OWL provides three increasingly expressive sublanguages OWL Full OWL DL OWL Lite

24. Comparison of versions  Full:  We get the full power of the OWL language.  It is very difficult to build a tool for this version.  The user of a fully-compliant tool may not get a quick and complete answer.  DL/Lite:  Tools can be built more quickly and easily  Users can expect responses from such tools to come quicker and be more complete.  We don't have access to the full power of the language.

25. Describing classes in OWL OWL vs. RDFS OWL allows greater expressiveness  Abstraction mechanism to group resources with similar characteristics  Much more powerful in describing constraints on relations between classes  Property transitivity, equivalence, symmetry, etc.  … Extensive support for reasoning

26. OWL Ontologies  What’s inside an OWL ontology Classes + class-hierarchy Properties (Slots) / values Relations between classes (inheritance, disjoints, equivalents) Restrictions on properties (type, cardinality) Characteristics of properties (transitive, …) Annotations Individuals  Reasoning tasks: classification, consistency checking

27. Classes  What is a Class? e.g., person, pet, old a collection of individuals (object, things,... ) a way of describing part of the world an object in the world (OWL Full)

28. owl:Class  Sub class of Class in RDF  Better to forget about classes of classes  Top-most class: owl:Thing

29. Individuals  Two equivalent declarations: 1.

30. Properties  What is a Property? e.g., has_father, has_pet, service_number a collection of relationships between individuals (and data) a way of describing a kind of relationship between individuals an object in the world (OWL Full)

31. OWL Properties Object Properties Ana  owns  Cuba Is range a literal / typed value ? then ERROR Data type Properties Ana  age  25  XML Schema data types supported DB people happy

32. Defining Properties  ObjectProperty  DatatypeProperty  rdfs:subPropertyOf  rdfs:domain  rdfs:range 

33. Describing classes in OWL Complex Classes Union of classes (owl:unionOf)  OR (A  B) Union of classes (owl:intersectionOf)  AND (A  B) Complement (owl:complementOf)  NOT Enumeration (owl:oneOf) Disjoint Classes (owl:disjointWith)

34. Describing classes in OWL Property Restrictions Defining a Class by restricting its possible instances via their property values OWL distinguishes between the following two:  Value constraint  Cardinality constraint

35. Describing classes in OWL Restrictions on Property Classes Properties:  allValuesFrom: rdfs:Class (lite/DL owl:Class)  hasValue: specific Individual  someValuesFrom: rdfs:Class (lite/DL owl:Class)  minCardinality: xsd:nonNegativeInteger (in lite {0,1})  maxCardinality: xsd:nonNegativeInteger (in lite {0,1})

36. What’s in OWL, but not in RDF  Ability to be distributed across many systems  Scalable to Web needs  Compatible with Web standards for: accessibility, and Internationalization  Open and extensible

37. Describing properties in OWL OWL vs. RDFS  RDF Schema provides some of predefined properties: rdfs:range used to indicate the range of values for a property. rdfs:domain used to associate a property with a class. rdfs:subPropertyOf used to specialize a property. …  OWL provides additional predefined properties: owl:cardinality (indicate cardinality) owl:hasValue (at least one of the specified property values) …  OWL provides additional property classes, which allow reasoning and inferencing: owl:FunctionalProperty owl:TransitiveProperty …

38. Describing properties in OWL OWL Property Classes rdf:Property owl:ObjectProperty owl:DatatypePropertyowl:FunctionalProperty owl:InverseFunctionalProperty owl:SymmetricProperty owl:TransitiveProperty  An ObjectProperty relates one Resource to another Resource.  A DatatypeProperty relates one Resource to a Literal - an XML Schema data type.

39. Transitivity of properties X  p 1  Y Y  p 1  Z implies X  p 1  Z  Transitivity existed already in RDF “subClassOf”, and ???  e.g. located_in, part_of

40. Symmetric properties X  p 1  Y implies X  p 1  Y  e.g., =

41. Functional Properties X  p 1  Y X  p 1  Z imply Z is the same as Y (they describe the same) What if Y, Z where explicitly defined as “different” ?

42. Inverse Functional Properties Y  p 1  A Z  p 1  A imply Z is the same as Y (they describe the same) What if Y, Z where explicitly defined as “different” ?

43. OWL distributed “equivalent class” “equivalent Property” Guitar Guitarra Internationalization standards ?

44. Complex Classes Male Students Married Female Professors Married Female Students Divorced Female Human Student Married Professor  Minority Students example

45. Disjoint Classes  Married disjoint with: Divorced Widowed Single  Are “Divorced” and “Single” disjoint ? Married Widowed Divorced Single

46. OWL Cardinality  min Cardinality  max Cardinality  “Cardinality” When min = max  has Value belongs to the class if it has the value

47. An Example OWL ontology

48. References  http://www.w3.org/TR/owl-ref/ http://www.w3.org/TR/owl-ref/  Chapter 8 of the book

49. The End