Ontology & OWL Semantic Web - Fall 2005 Computer Engineering Department Sharif University of Technology Outline Introduction & Definitions Ontology Languages OWL 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). Ontologies Ontologies (contd.) Ontologies are about vocabularies and their meanings, with explicit, expressive, and welldefined semantics, possibly machineinterpretable. “Ontology is a formal specification of a conceptualization.” Gruber, 1993 Main elements of an ontology: Concepts Relationships Hierarchical Logical Properties Instances (individuals) 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 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 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) Meaning is in Connections is made from G a m e Grape a i n r f W Wine m s d e i e r o p For machines... The meaning of the document is not defined. Machines cannot understand it. Wine is made from Grape We are defining the structure of document by XML but now the meaning of the structure is not defined. <Sentence> <Subject> Wine </Subject> <Verb> is made from </Verb> <Object> Grape </Object> </Sentence> XML document <Sentence> <Subject> Wine </Subject> <Verb> is made from </Verb> <Object> Grape </Object> </Sentence> Ontology gives the meaning... Natural Language Document <Sentence> <Subject> Wine </Subject> <Verb> is made from </Verb> <Object> Grape </Object> </Sentence> Ontology Why develop ontologies? To share knowledge To reuse domain knowledge E.g., geography ontology To make domain assumptions explicit E.g., using an ontology for integrating terminologies Facilitate knowledge management Enable new users to learn about the domain To distinguish domain knowledge from operational knowledge e.g., biblio metadata What they are good for Informal Controlled vocabulary Upper-level structures for extending further E.g., IRS information search Search E.g., AGRIS/CARIS categorization Browsing support Beginnings of interoperability Limited query expansion disambiguation e.g., “Jordan” as a name of Basket-ball player and name of a country What they are good for Formal Search Concept-based query User uses own words, language Consistency checking Related terms Intelligent query expansion: “fishing vessels in China” expands to “fishing vessels in Asia” 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 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 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) Object oriented model 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 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. Origins of OWL DARPA Agent Markup DAML Language EU/NSF Joint Ad hoc Committee A W3C Recommendation OIL Ontology Inference Layer RDF DAML+OIL OWL All influenced by RDF OWL Lite OWL DL OWL Full OWL OWL and RDF Schema enable rich machine-processable semantics RDFS OWL Semantics <rdfs:Class rdf:ID="River"> <rdfs:subClassOf rdf:resource="#Stream"/> </rdfs:Class> RDF Schema XML/DTD/XML Schemas Syntax OWL <owl:Class rdf:ID="River"> <rdfs:subClassOf rdf:resource="#Stream"/> </owl:Class> 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 OWL Design Goals Shared ontologies Ontology evolution Ontology interoperability Inconsistency detection Expressivity vs. scalability Ease of use Compatibility with other standards Internationalization Versions of OWL Depending on the intended usage, OWL provides three increasingly expressive sublanguages OWL Full OWL DL OWL Lite Full: Very expressive, no computation guarantees DL (Description Logic): Maximum expressiveness, computationally complete Lite: Simple classification hierarchy with simple constraints. 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. 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 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 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) owl:Class Sub class of Class in RDF Better to forget about classes of classes Top-most class: owl:Thing <owl:Class rdf:ID=“Person"/> <owl:Class rdf:ID=“Man"> <rdfs:subClassOf rdf:resource="#Person" /> </owl:Class> Individuals Two equivalent declarations: 1. <Person rdf:ID=“Ganji" /> 1. <owl:Thing rdf:ID=“Ganji" /> <owl:Thing rdf:about="#Ganji"> <rdf:type rdf:resource="#Person"/> </owl:Thing> 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) OWL Properties Object Properties Data type Properties Ana owns Cuba Ana age 25 Is range a literal / typed value ? then ERROR XML Schema data types supported DB people happy Defining Properties ObjectProperty DatatypeProperty rdfs:subPropertyOf rdfs:domain rdfs:range <owl:ObjectProperty rdf:ID="madeFromGrape"> <rdfs:domain rdf:resource="#Wine"/> <rdfs:range rdf:resource="#WineGrape"/> </owl:ObjectProperty> Describing classes in OWL Complex Classes Union of classes (owl:unionOf) Union of classes (owl:intersectionOf) OR (A B) AND (A B) Complement (owl:complementOf) NOT Enumeration (owl:oneOf) Disjoint Classes (owl:disjointWith) 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 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}) 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 Describing properties in OWL OWL vs. RDFS RDF Schema provides some of predefined properties: OWL provides additional 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: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 … Describing properties in OWL OWL Property Classes rdf:Property owl:ObjectProperty owl:SymmetricProperty owl:DatatypeProperty owl:FunctionalProperty owl:InverseFunctionalProperty owl:TransitiveProperty An ObjectProperty relates one Resource to another Resource. A DatatypeProperty relates one Resource to a Literal - an XML Schema data type. Transitivity of properties X p1 Y Y p1 Z implies X p1 Z Transitivity existed already in RDF “subClassOf”, and ??? e.g. located_in, part_of Symmetric properties X p1 Y implies X p1 Y e.g., = Functional Properties X p1 Y X p1 Z imply Z is the same as Y (they describe the same) What if Y, Z where explicitly defined as “different” ? Inverse Functional Properties Y p1 A Z p1 A imply Z is the same as Y (they describe the same) What if Y, Z where explicitly defined as “different” ? OWL distributed “equivalent class” “equivalent Property” Guitar Guitarra Internationalization standards ? Complex Classes Female Student Professor Married Human Male Students Married Female Professors Minority Students example Married Female Students Divorced Disjoint Classes Married disjoint with: Married Divorced Widowed Single Divorced Widowed Single Are “Divorced” and “Single” disjoint ? OWL Cardinality min Cardinality max Cardinality “Cardinality” When min = max has Value belongs to the class if it has the value An Example OWL ontology <owl:Class rdf:ID=“Person” /> <owl:Class rdf:ID=“Man”> <rdfs:subClassOf rdf:resource=“#Person” /> <owl:disjointWith rdf:resource=“#Woman” /> </owl:Class> <owl:Class rdf:ID=“Woman”> <rdfs:subClassOf rdf:resource=“#Person” /> <owl:disjointWith rdf:resource=“#Man” /> </owl:Class> <owl:Class rdf:ID=“Father”> <rdfs:subClassOf rdf:resource=“Man” /> <owl:Restriction owl:minCardinality="1"> <owl:onProperty rdf:resource="#hasChild" /> </owl:Restriction> </owl:Class> <owl:ObjectProperty rdf:ID=“hasChild"> <rdfs:domain rdf:resource="#Parent" /> <rdfs:range rdf:resource="#Person" /> </owl:ObjectProperty> References http://www.w3.org/TR/owl-ref/ Chapter 8 of the book The End