The 2 nd International Semantic Web Conference (ISWC03)

1. The 2nd International Semantic Web Conference (ISWC03) 20-23 october 2003 Sanibel Island (Florida) Michele Missikoff Federica Schiappelli

2. Summary • The conference program • Overview of the Semantic Integration workshop • The main conference • Keywords for the Semantic Web • Roadmap (by Tim Berners Lee)

3. The conference “events” • Tutorials • Workshops • Keynote speaches • Panels • Main conference • Posters presentation • Semantic web challenge http://iswc2003.semanticweb.org/

4. Tutorials (on Monday, 20 oct.) • Agent-Mediated Semantic Web/Grid ServicesKatia Sycara and Terry Payne • Tutorial on OWL Peter F. Patel-Schneider, Ian Horrocks, and Sean Bechhofer • Creating Ontologies and Semantic Web Applications with ProtégéHolger Knublauch and Natasha F. Noy • Information Integration on the World Wide Web Heiner Stuckenschmidt, Ubbo Visser, Holger Wache http://iswc2003.semanticweb.org/pdf/Protege-OWL-Tutorial-ISWC03.pdf http://webode.dia.fi.upm.es/iswc03/

5. Workshops (on Monday, 20 oct.) • Practical and Scalable Semantic Systems • SemanticIntegration • Semantic Web Technologies for Searching and Retrieving Scientific Data • Human Language Technology for the Semantic Web and Web Services • Rules and Rule Markup Languages for the Semantic Web • Evaluation of Ontology-Based Tools

6. Summary • The conference program • Overview of the Semantic Integration workshop • The main conference • Keywords for the Semantic Web • Roadmap (by Tim Berners Lee)

7. The information integration problem

8. The Semantic Integration workshop • In the Semantic Web context, the information are described by multiple ontologies and schemas • Matching between ontologies and schemas is still largely done by hand • Numerous research activities on methods for describing mappings, manipulating them, and generating them semi-automatically Electronic proceedings: http://ceur-ws.org/Vol-82/ Invited talks (slides): http://smi.stanford.edu/si2003/invitedTalksAbstracts.html

9. Keynote Speeches and Panels (on Monday, 20 oct., during the workshop) • Semantic Web Scenarios involve rendez-vous between peers • Requires mappings between their ontologies • Generate mappings • Translate between ontology languages • Maintain mappings as ontologies change • The same problems as database schema integration, BUT • Current approaches to data management are not enough: language-specific; problem-specific Philip A. BernsteinMicrosoft Research Generic Model Management: A Database Infrastructure for Schema Manipulation

10. A specific solution proposed by Bernstein • A generic approach: model management • operators to manipulate models and mappings as bulk objects • Amodel is a rooted directed graph, which represents a complex information structure • A mapping is a model that represents a transformation between two models… • …Or it could be a binary table (a morphism) • Schema matching (mapping discovery) • Given two schemas, return correspondences that specify pairs of related elements (lexical-structural-superclasses alignement) • Semantic Mapping • Given correspondences between two schemas, return an expression that translates instances of one schema into instances of the other. • Model Merging • Use the mapping to guide the merging

11. Keynote Speeches and Panels (on Monday, 20 oct., during the workshop) – cont’d Two principal paths for info integration • Using a central structure as ‘interlingua’ • Problems: • Creating the central structure (coverage, consistency, updating) • Linking sources and targets to it (automatically?) • Benefits: • Linear (2N) in number of sources/targets • Creating individual source-to-target mappings • Problems: • Creating and updating the mappings (automatically?) • N2 in number of sources/targets • Benefits: • Doesn’t require general one-size-fits-all model/structure Edward Hovy Information Sciences Institute of the University of Southern California Building Large Ontologies

12. Hovy’s approach • The Interlingua route: toward a mergedontology • General alignment and merging problem • Given many domain models—how can you integratethem consistently, without overlap or redundancy? • The Transfer route: toward learningindividual mappings • aligning databases directly Solution: Use a large general-purpose concept network to provide thebackground—the SENSUSOntology. Improving alignment byenriching content by addingdefinitional material and by clustering entities.

13. Summary • The conference program • Overview of the Semantic Integration workshop • The main conference • Keywords for the Semantic Web • Roadmap (by Tim Berners Lee)

14. Invited Speakers (during the main conference) • Jim Hendler: On Beyond Ontology: Returning to AI from the Semantic Web • Michael Brodie: The Long and Winding Road To Industrial Strength Semantic Web Services • Tim Berners-Lee: SemanticWeb:Where to direct our energy?

15. Jim Hendler’s talk • Director of a University of Maryland's lab; cochair of the W3C Web Ontology Working Group • his research group developed SHOE; creator of DARPA's DAML program • “…it's beginning to look like we may be successful!” • OWL, the Web recommended ontology language • Logic toolkits are produced by software companies • Time for us to think more about what we do with all this • Today Challenges: • Integration… partial mapping • Process modelling … WSBPEL, OGSA, etc. • Temporal logic • OWL feeding • Common agreement for ontology building • Semantic Web technology available to vendors Electronic proceedings: http://ceur-ws.org/Vol-82/ Invited talks (slides): http://smi.stanford.edu/si2003/invitedTalksAbstracts.html

16. Michael Brodie’s talk • Chief Scientist, Verizon Information Technology • industrial researcher, focussing on advanced computational models and architectures, the large-scale information systems that they support, business and technical contexts • “Web Services: the basis for the Next Generation of computing !” • flexible • can be discovered and invoked anywhere • composed, as required, to achieve higher level goals • proposed to address software integration • Today Challenges: • overcome the integration challenge on an industrial scale • technical pragmatics such as scalability and performance dominate http://iswc2003.semanticweb.org/invitedtalks.html

17. Tim Berners-Lee’s talk • The Semantic Web inventor! Speaking too fast… didn’t understand anything… See the conclusions!!!

18. The main conference • Principal themes • Foundations • Ontological reasoning • Semantic web services • Security, trust and privacy • Agents and the Semantic Web • Information Retrieval • Multi-media • Tools and methodologies • Applications • Industrial Track

19. Summary • The conference program • Overview of the Semantic Integration workshop • The main conference • Keywords for the Semantic Web • Roadmap (by Tim Berners Lee)

20. Interesting themes • Interoperability • Contexts • Languages: RDF(S); OWL • Reasoning with DL • Web services…composition?

21. Interoperability • Semantic coordination (solution by Trento univ.) • Semantic models considered are hierarchical classifications, represented as labelled graphs • Logical formulae are built taking into consideration • lexical knowledge (words in labels), • domain knowledge (relations bw concepts represented by labels), • structural knowledge (isa hierarchy). • Shift from computing linguistic and structural similarity to the problem of deducing relations bw sets of logical formulae, encoding the meaning of the involved entities (nodes on the graph) P. Bouquet University of Trento Semantic Coordination

22. Contexts • Context is a model of some domain, which encode a particular view • Context is local (reduced sharability) • Mapping among contexts is the issue Contextual Ontologies = Ontology + context mapping Fausto Giunchiglia University of Trento C-OWL: Contextualizing Ontologies

23. Languages: RDF(S) • RDF(S)has a non standard meta-modelling architecture • Multiple modelling primitives seem to be represented by the same RDFS primitive (e.g. rdf:type, rdf:subClassOf) • A Fixed meta-modelling architecture has been proposed I.Horrocks F.Patel-Schneider University of Manchester RDFS(FA) and RDF MT: two semantics for RDF

24. Parent Restriction hasChild subClassOf onProperty minCardinality 1 equivalentClass Federica subClassOf Francesco subPropertyOf worksWith subClassOf Class Resource type A non standard meta-modelling architecture • RDF(S)is used to add metadata annotations to Web res. • Subject-predicate-object triples used to link resources • i.e., triples represent knowledge about domain (such as Federica worksWith Francesco) • RDF(S) also used to define syntax and semantics of subsequent language layers (and even of itself), e.g.:

25. Problems with RDF MT • Not clearthat RDF(S) is appropriate for bothfunctions (at once) • Uniform semantic treatment of triple syntax • i.e., “syntax” and “knowledge” triples have same semantics • Confusing (for some) cyclical meta-model • Semantics given by “non-standard”Model Theory Should I use owl:Class or rdfs:Class? rdfs:Resource instance of rdfs:Class rdfs:Class subclass of rdfs:Resource …Resource is instance of its subclass?? • More expressive ontology languages layered on top of RDF(S) • E.g., OIL, DAML+OIL, and now OWL

26. RDFS(FA) • RDFS(FA) is a sub-language of RDF(S) • It stands for “RDFS with Fixed layer meta-modeling Architecture” • HasaFirst Order/Description Logic style semantics • The universe of discourse is divided up into a series of strata • User defined facts, vocabulary and RDF/OWL built-in vocabulary are (typically) in different strata • Each modelling primitive belongs to a certain stratum (layer) • Labelled with different prefixto indicate the stratum

27. RDFS(FA) layers fa:MResource, fa:MClass fa:MProperty … Stratum 3 (Meta-Language Layer) fa:LResource, fa:LClass fa:LProperty … Stratum 2 (Language Layer) fa:OResource Person, Researcher workWith … Stratum 1 (Ontology Layer) Stratum 0 (Instance Layer) Federica, Francesco…

28. Advantages of RDFS(FA) • No problems layering FO languages on top of RDFS(FA) • RDFS(FA) supports use of meta-classes and meta-properties • In stratum above classes and properties • RDFS(FA) metamodel very similar to that of UML • Possible to define a new sub-language of OWL: OWL FA • Extends OWL DL with meta-classes/properties • Fully compatible with OWL DL semantics • Reasoning (even for meta-classes/properties)

29. Reasoning with DL • Reasoning with ontology languages is important to exploit the semantics of ontology-based annotations • Instance checking • Subsumption (taxonomic) reasoning • Used in SW applications • E.g. search engines, matchmaking of services, document classification, etc… • OWL is strictly related to Description Logics • DL provides such reasoning facilities I.Horrocks F.Patel-Schneider University of Manchester Reducing OWLentailment to DL satisfiability

30. Web services (?) • Karlsruhe: • WS Composition is a planning problem or pre-/post-cond matching • OntoMat-Service (tool for WS workflow) • BPEL4WS (Stanford Univ.)Coreography Fwk • BPEL (programming lang) to specify the sequence of tasks • Partner selected at runtime • Automatic semantic translation S.Agarwal, S.Handschuluh, S.Staab University of Karlsruhe Surfing the Service Web D.J.Mandell, S.McIlraith University of Stanformd Adapting BPEL4WS for teh SW: the bottom-up approach to ws interoperation

31. Summary • The conference program • Overview of the Semantic Integration workshop • The main conference • Keywords for the Semantic Web • Roadmap (by Tim Berners Lee)

32. SW status • OWL becomes stable • Steadily growing deployment of RDF • Growing SWeb-specific industry sector • SW Services starting to take off

33. Risks • Architecture becomes fractured, weak, or baroque • Fracture between Web and S/Web arch • Fragmentation in query and rules • RDF/XML syntax shock • Perceived relationships between SW and WS • Deployment in real products

34. The Killer App for the Semantic Web • It’s the integration!!! • Guidelines • Be careful of terms - ontology, semantics, etc • Explaining how communities interact • Please re-use • Don't create new URI schemes • Don't re-invent HTTP space • Don't re-invent RDF • Don't re-invent ontologies where they exist

35. Where to direct our energy? • Indexing data - by ontology • Indexing rules, building translation paths • like one big database? or one big web? • SW and WS • Discovery should be SemWeb-based • Balances • Engineering vs Research • Getting it working vs getting it right • Tractable Machinery vs Heuristics

36. Thank you for the attention Mmm mm