1. Xiang Zhang Feb 25 th, 2011 RDF, RDFS, OWL and the Semantic Web

2. Today’s Web A system of interlinked hypertext Information is accessed via keyword-based search and browser Browsers render information for human consumption

3. Binary objects serialization Relational databases Extensible Markup Language (XML) And what… Information Sharing

4. Making web-based information machine understandable Providing a rich semantic model for expressing domain knowledge Enabling cross-domain information exchange Motivations of the Semantic Web

5. The Semantic Web Stack Hypertext Web technologies URI Unicode XML *Source: http://en.wikipedia.org/wiki/Semantic_Web_Stack

6. The Semantic Web Stack Hypertext Web technologies URI Unicode XML Standardized Semantic Web technologies RDF RDFS OWL SPARQL *Source: http://en.wikipedia.org/wiki/Semantic_Web_Stack

7. The Semantic Web Stack Hypertext Web technologies URI Unicode XML Standardized Semantic Web technologies RDF RDFS OWL SPARQL Unrealized Semantic Web technologies RIF/SWRL Cryptography Trust User Interface *Source: http://en.wikipedia.org/wiki/Semantic_Web_Stack

8. The Semantic Web Stack Standardized Semantic Web technologies RDF RDFS OWL *Source: http://en.wikipedia.org/wiki/Semantic_Web_Stack

9. RDF is a general purpose data model for exchange of machine-understandable information in the Web What does RDF support? –Represent metadata about Web objects –Facilitate data merge –Support evolution of data schemas RDF – Resource Description Framework

10. RDF Statement ResourcePredicateObject or The data model Resource Property Resource Literals Resource : anything with an associated URIRef http://www.restaurant.org/food-ont#Pizza https://sosa.ucsd.edu/confluence/display/~xiang Property : a resource that serves as a predicate in a statement http://www.mydomain.org/web-page-owner Object : a resource or a literal “$3.5”, “123”, xsd:integer^^10 Vocabulary : a set of URIrefs Elements in a vocabulary are unique

11. An example of an RDF model Legend Purple Box: Resource Green Box: Literal Red arcs: Property advisedBy: http://www.sosa.ucsd.edu/rel ation#advisedBy FN: http://www.w3.org/2001/vcar d-rdf/3.0#FN

12. Data Merge Using RDF Merge Them… Why does it work?

13. Which URI should we use and how to find them? –Popular ones! Data merge can take place automatically. –A good place to find popular URIs Linking Open Data Community Project: http://www.w3.org/wiki/SweoIG/TaskForces/CommunityProjects/LinkingOpenData http://www.w3.org/wiki/SweoIG/TaskForces/CommunityProjects/LinkingOpenData Use of URIs Picture Source: http://www.w3.org/wiki/SweoIG/TaskForces/CommunityProjects/LinkingOpenDatahttp://www.w3.org/wiki/SweoIG/TaskForces/CommunityProjects/LinkingOpenData

14. RDF is too general to incorporate semantics –it only provides syntax for data exchange in the Web RDF is not enough… 1. What if we replace advisedBy with propertyA, and FN with propertyB? 2. What if we want to know if “Celal” and “Xiang” are similar? 3. What is the domain of the property “advisedBy” ?

15. An ontology defines: –a specific vocabulary used to describe a certain reality, plus –a set of explicit assumptions regarding the intended meaning of the vocabulary An ontology describes a formal specification of a certain domain –Shared understanding of a domain of interest –Machine manipulable model of a domain of interest A popular definition –An explicit specification of a conceptualization [Tome Gruber] Introduction to ontology in computer science* * www.co-ode.org/resources/tutorials/intro/slides/Introduction.ppt

16. RDFS provides a framework to describe domain-specific classes, properties and individuals. –Features for describing classes which represent concepts –Features for describing properties with restrictions Constructs for describing classes –rdfs:Class –rdfs:subClassOf Constructs for describing properties –rdfs:domain –rdfs:range –rdfs:subPropertyOf RDFS has more constructs… –more info: http://www.w3.org/TR/rdf-schema/http://www.w3.org/TR/rdf-schema/ RDF Schema – A vocabulary language for RDF

17. Type inheritance –Morris is an instance of Cat; Cat is a subClassOf Mammal ->Morris is an instance of Mammal Type Inference –teaches is a property whose domain is Teacher and Range is Student; Bob teaches Tom -> Bob is a teacher and Tom is a student Transitivity –Dog is a subClassOf Mammal; Mammal is a subClassof Animal -> Dog is a subClassOf Animal RDFS Reasoning Capabilities * *http://www.ksl.stanford.edu/software/jtp/doc/owl-reasoning.html

18. What about the following features: –Property cardinality –Class/Property equivalence –Inverse property –Class combinations (union, intersection, complement) –… A language with a richer set of constructs is needed. RDF/RDFS is not enough too…

19. OWL is the latest standard in ontology languages from the World Wide Web Consortium (W3C) OWL is built on top of RDF/RDFS OWL has a richer set of modeling constructs Three species of OWL: –OWL Lite: only uses a subset of OWL constructs –OWL DL: uses all OWL constructs but with limitations to achieve computational decidability –OWL Full: uses all OWL features with no computational guarantee OWL profiles: OWL-EL, OWL-QL, OWL RL OWL – Web Ontology Language

20. Classes –Named classes(available in RDFS) –Restriction(anonymous ) classes –Intersection classes –Union classes –Complement classes –Equivalent classes –DisjointOf class –Enumerated classes Basic elements of OWL (not all) Properties –Transitive –Symmetric –Functional –Inverse –Inverse Functional –allValuesFrom –someValuesFrom –Cardinality –hasValue Individuals A complete list can be found here: http://www.w3.org/TR/owl-features/

21. A restriction class example A restriction class that imposes “has value of Red” on property “hasColor”.

22. Including all RDFS reasoning capabilities, plus Transitivity (different from RDFS) Inheritance of disjointness constraint –Plant is disjoint with Animal, and Mammal is a subclass of Animal ->Plant is disjoint with Mammal Inferring equivalent relationship via FunctionalProperty –mother is a FunctionalProperty, Joe’s mother is Julie, Joe’s mother is Maggie -> Julie and Maggie is equivalent If an object is an instance of a restriction class, then the object has the specified value for that property –A restriction class called WhiteSkinPeople has a hasValue property called skinColor whose value is White, Joe is an instance of WhiteSkinPeople -> Joe has White skinColor Reasoning with inverseOf –owns and ownedby Any many more… OWL inference capabilities (only a small part of them)* *http://www.ksl.stanford.edu/software/jtp/doc/owl-reasoning.html

23. An inference example - the domain model* *Adapted from “Semantic Web Programming” chapter 5, by John Hebeler etc. Brief descriptions of the domain model: 1.Mammal 2.Human is a subclass of Mammal 3.Canine is a subclass of Mammal and is equivalent to the class of instances for which there is at least one breed property with a value that is an instance of Breed 4.Breed 5.LargeBread is a subclass of Bread 6.SmallBread is a subclass of Bread 7.GoldenRetriever 8.Chihuahua 9.PetOfRyan is a subclass of Mammal and it’s instances have a property that has a value of Ryan 10.hasOwner 11.owns is inverse of hasOwner 12.Ryan is a Human whose name is “Ryan Blace” and owns Daisy 13.Daisy is a Canine that has a property breed with the value GoldenRetriever 14.Amber is a Mammal that has a property breed with the value GoldenRetriever Not for human consumption

24. An inference example – no inference* Brief descriptions of the domain model: 1.Mammal 2.Human is a subclass of Mammal 3.Canine is a subclass of Mammal and is equivalent to the class of instances for which there is at least one breed property with a value that is an instance of Breed 4.Breed 5.LargeBread is a subclass of Bread 6.SmallBread is a subclass of Bread 7.GoldenRetriever 8.Chihuahua 9.PetOfRyan is a subclass of Mammal and it’s instances have a property that has a value of Ryan 10.hasOwner 11.owns is inverse of hasOwner 12.Ryan is a Human whose name is “Ryan Blace” and owns Daisy 13.Daisy is a Canine that has a property breed with the value GoldenRetriever 14.Amber is a Mammal that has a property breed with the value GoldenRetriever *Adapted from “Semantic Web Programming” chapter 5, by John Hebeler etc.

25. An inference example – RDFS inference* Brief descriptions of the domain model: 1.Mammal 2.Human is a subclass of Mammal 3.Canine is a subclass of Mammal and is equivalent to the class of instances for which there is at least one breed property with a value that is an instance of Breed 4.Breed 5.LargeBread is a subclass of Bread 6.SmallBread is a subclass of Bread 7.GoldenRetriever 8.Chihuahua 9.PetOfRyan is a subclass of Mammal and it’s instances have a property that has a value of Ryan 10.hasOwner 11.owns is inverse of hasOwner 12.Ryan is a Human whose name is “Ryan Blace” and owns Daisy 13.Daisy is a Canine that has a property breed with the value GoldenRetriever 14.Amber is a Mammal that has a property breed with the value GoldenRetriever *Adapted from “Semantic Web Programming” chapter 5, by John Hebeler etc.

26. An inference example – OWL-DL inference* Brief descriptions of the domain model: 1.Mammal 2.Human is a subclass of Mammal 3.Canine is a subclass of Mammal and is equivalent to the class of instances for which there is at least one breed property with a value that is an instance of Breed 4.Breed 5.LargeBread is a subclass of Bread 6.SmallBread is a subclass of Bread 7.GoldenRetriever 8.Chihuahua 9.PetOfRyan is a subclass of Mammal and it’s instances have the hasOwner property that has a value of Ryan 10.hasOwner 11.owns is inverse of hasOwner 12.Ryan is a Human whose name is “Ryan Blace” and owns Daisy 13.Daisy is a Canine that has a property breed with the value GoldenRetriever 14.Amber is a Mammal that has a property breed with the value GoldenRetriever *Adapted from “Semantic Web Programming” chapter 5, by John Hebeler etc.

27. A list of editors and reasoners (a lot…): –http://www.w3.org/2007/OWL/wiki/Implementationshttp://www.w3.org/2007/OWL/wiki/Implementations Protégé: an ontology editor –create, edit, combine, reason, serialize, visualize ontologies –reasoner is pluggable Jena: a framework to provide a programmatic environment for RDF, RDFS and OWL Reasoners: –FaCT++: supports OWL DL, open-source –Pellet: supports DL, EL, open-source RDF Gravity: RDF document visulizer Ontology authoring tools and reasoners

28. THANK YOU!