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Ontologies? Semantic Web? OWL? – Making sense of it all

Ontologies? Semantic Web? OWL? – Making sense of it all. Presenters Femke.Ongenae@intec.ugent.be Matthias.Strobbe@intec.ugent.be Stijn.Verstichel@intec.ugent.be www.ibcn.intec.ugent.be INTEC Broadband Communication Networks (IBCN) Department of Information Technology (INTEC)

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Ontologies? Semantic Web? OWL? – Making sense of it all

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  1. Ontologies? Semantic Web? OWL? – Making sense of it all Presenters Femke.Ongenae@intec.ugent.be Matthias.Strobbe@intec.ugent.be Stijn.Verstichel@intec.ugent.be www.ibcn.intec.ugent.be INTEC Broadband Communication Networks (IBCN) Department of Information Technology (INTEC) Ghent University - IBBT

  2. The ontology cloud Formal logic SWRL Reasoning Ontology SPARQL Semantic Web RDF OWL

  3. The evolution of the Web Intelligent Web Web 4.0 Web OS 2020 - 2030 Intelligent personal agents Web 3.0 Semantic Web Distributed Search SWRL OWL 2010 - 2020 SPARQL Semantic Databases AJAX OpenID Connections between Information Semantic Search Social Web ATOM Widgets RSS RDF Mashups P2P Web 2.0 Office 2.0 Javascript Flash SOAP XML Weblogs Social Media Sharing 2000 - 2010 The Web Java HTML SaaS Social Networking HTTP Directory Portals Wikis VR Keyword Search Lightweight Collaboration Web 1.0 The PC BBS Websites Gopher 1990 - 2000 MacOS SQL MMO’s Groupware SGML Databases Windows File Servers The Internet PC Era Email IRC 1980 - 1990 FTP USENET PC’s File Systems Connections between people

  4. The limitations of keyword search The Intelligent Web Web 4.0 2020 - 2030 Reasoning Productivity of Search The Semantic Web Web 3.0 Semantic Search 2010 - 2020 The Social Web Natural language search Web 2.0 The World Wide Web 2000 - 2010 Tagging Web 1.0 1990 - 2000 Keyword search The Desktop Directories PC Era 1980 - 1990 Files & Folders Databases Amount of data

  5. Semantic Web – Adding meaning to data • Different methods to add semantics to data: • Tagging • Statistics • Linguistics • Ontology – Semantic Web • AI • Semantic Web: Set of open standards by the W3C to add semantics (meaning) to data

  6. Ontology - OWL “Anontology is a specification of a conceptualizationin the context of knowledgedescription” has_topping * Pizza Meat Is a Spiciness Salami Vegetarian Pizza Pizza Not(has_toppingsomeMeat)

  7. Ontology - OWL • Structuredknowledgerepresentation • Domain  Application • Sharing – Reuse • Support communication • Captureknowledgeformally • Reasoning • Extract newknowledge

  8. Femke IBCN Works_at RDF – Store data as “triples” • the subject, which is an RDF URI reference or a blank node • the predicate, which is an RDF URI reference • the object, which is an RDF URI reference, a literal or a blank node Predicate Subject Object

  9. The semantic graph connects everything… People Companies Emails Places Products Interests Services Web Pages Activities Documents Projects Events Multimedia Groups The Semantic Web The social graph just connects people Better search More targeted ads Smarter collaboration Deeper integration Richer content Better personalization

  10. SWRL - SPARQL • SWRL • Define rules by using domain concepts • Add more expressivity then pure OWLPerson(?p) ^ hasSalaryInPounds(?p, ?pounds) ^ swrlb:multiply(1.9, ?pounds, ?dollars) -> hasSalaryInDollars(?p, ?dollars) • SPARQL • Query data • Similar to SQL but optimized for RDF dataPREFIX foaf: <http://xmlns.com/foaf/0.1/> SELECT ?name WHERE { ?person foaf:mbox <mailto:alice@example.net> . ?person foaf:name ?name . }

  11. Layered cake of the Semantic Web Reasoning SWRL & SPARQL OWL Data triples

  12. Tutorial: Building an OWL Ontology Department of Information Technology – Broadband Communication Networks (IBCN)

  13. Named & Disjoint Classes Department of Information Technology – Broadband Communication Networks (IBCN)

  14. Class Hierarchy Department of Information Technology – Broadband Communication Networks (IBCN)

  15. Object Properties Department of Information Technology – Broadband Communication Networks (IBCN)

  16. Object Property Characteristics Department of Information Technology – Broadband Communication Networks (IBCN)

  17. Property Domains & Ranges Department of Information Technology – Broadband Communication Networks (IBCN)

  18. Property Restrictions • A restriction describes an anonymous class of individuals based on the relationships that members of the class participate in. • 3 main categories: • Quantifier Restrictions • Existential restrictions • Universal restrictions • Cardinality Restrictions • hasValue Restrictions Department of Information Technology – Broadband Communication Networks (IBCN)

  19. Existential Restriction Department of Information Technology – Broadband Communication Networks (IBCN)

  20. Reasoning • Key Features • Classification: • Test whether or not one class is a subclass of another class • Consistency checking • Check whether or not it is possible for a class to have any instances Department of Information Technology – Broadband Communication Networks (IBCN)

  21. Consistency Checking Department of Information Technology – Broadband Communication Networks (IBCN)

  22. Necessary & Sufficient Conditions • Primitive Class • Class that only has ‘necessary’ conditions • Defined Class • Class that has at least one set of ‘necessary and sufficient’ conditions Department of Information Technology – Broadband Communication Networks (IBCN)

  23. Automated Classification Computing subclass- superclass relationships vital to keep large ontologies in logically correct state Department of Information Technology – Broadband Communication Networks (IBCN)

  24. Universal Restrictions • Constrain the relationships along a given property to individuals that are members of a specific class • They don’t specify the existence of a relationship Department of Information Technology – Broadband Communication Networks (IBCN)

  25. Open World Assumption • It cannot be assumed that something does not exist until it is explicitly stated that it does not exist! •  Closed World Assumption (programming languages, databases, …) Department of Information Technology – Broadband Communication Networks (IBCN)

  26. Closure Axiom Department of Information Technology – Broadband Communication Networks (IBCN)

  27. Value Partition • Restricting the possible values for a property to an exhaustive list • Design Pattern Department of Information Technology – Broadband Communication Networks (IBCN)

  28. Value Partition Department of Information Technology – Broadband Communication Networks (IBCN)

  29. Cardinality Restrictions • For property P, cardinality restrictions describe the minimum, maximum or exact number of P relationships that an individual can participate in Department of Information Technology – Broadband Communication Networks (IBCN)

  30. Qualified Cardinality Restriction Department of Information Technology – Broadband Communication Networks (IBCN)

  31. Datatype Properties Department of Information Technology – Broadband Communication Networks (IBCN)

  32. Data Properties Department of Information Technology – Broadband Communication Networks (IBCN)

  33. Open World Reasoning bis Department of Information Technology – Broadband Communication Networks (IBCN)

  34. Open World Reasoning bis Department of Information Technology – Broadband Communication Networks (IBCN)

  35. hasValue Restriction Department of Information Technology – Broadband Communication Networks (IBCN)

  36. Enumerated Classes Department of Information Technology – Broadband Communication Networks (IBCN)

  37. Multiple Sets of Necessary & Sufficient Conditions Department of Information Technology – Broadband Communication Networks (IBCN)

  38. Ontologies – more than just a datamodel … but !

  39. Important Consideration ONTOLOGY ≠ DATA-MODEL ONTOLOGY = DOMAIN-MODEL

  40. Three common layers +/- STATIC REUSE DYNAMIC LOGIC

  41. What do you need in an ontology-based application? SHARED ONTOLOGY MODEL

  42. Typical Ontology Service SPARQL SPARQL SPARQL JOSEKI RDF123 JENA D2RQ TDB SDB Spreadsheet MySQL PopulatorE PopulatorA PopulatorB PopulatorC PopulatorD

  43. D2R-Server: TreatingNon-RDF Databases as Virtual RDF Graphs

  44. RDF123 is an application and web service to generate RDF data from spreadsheets

  45. Recent commercial initiatives • Ontology.com • Thinking Service Models • Metatomix • Semantic web-based solutions for Enterprise Resource Interoperability • TopQuadrant • Making Information Work for the Enterprise • Semantic Discovery Systems • Beyond Business Intelligence, from Analytics to Discovery • Oracle 11g • Open, scalable, secure and reliable RDF management

  46. Every feature at a certain cost

  47. Questions ? Some slides and graphs borrowed from the presentation “Making sense of the Semantic Web” by Nova Spivack http://www.mindingtheplanet.net Presenters Femke.Ongenae@intec.ugent.be Matthias.Strobbe@intec.ugent.be Stijn.Verstichel@intec.ugent.be www.ibcn.intec.ugent.be INTEC Broadband Communication Networks (IBCN) Department of Information Technology (INTEC) Ghent University - IBBT

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