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
2、 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 Services Katia Sycara and Terry Payne Tutorial on OWL Peter F. Patel-Schneide
3、r, Ian Horrocks, and Sean Bechhofer Creating Ontologies and Semantic Web Applications with Protg Holger 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:
4、/webode.dia.fi.upm.es/iswc03/,5,Workshops (on Monday, 20 oct.),Practical and Scalable Semantic Systems Semantic Integration 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 S
5、emantic 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 c
6、ontext, the information are described by multiple ontologies and schemasMatching between ontologies and schemas is still largely done by handNumerous research activities on methods for describing mappings, manipulating them, and generating them semi-automatically,Electronic proceedings: http:/ceur-w
7、s.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 betwe
8、en 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. Bernstein Microsoft Research Generic Model Management: A Database Infrastructure for
9、Schema Manipulation,10,A specific solution proposed by Bernstein,A generic approach: model management operators to manipulate models and mappings as bulk objects A model is a rooted directed graph, which represents a complex information structure A mapping is a model that represents a transformation
10、 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 expre
11、ssion 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) contd,Two principal paths for info integration Using a central structure as interlingua Problems: Cre
12、ating 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/targ
13、ets Benefits: Doesnt require general one-size-fits-all model/structure,Edward Hovy Information Sciences Institute of the University of Southern California Building Large Ontologies,12,Hovys approach,The Interlingua route: toward a merged ontology General alignment and merging problem Given many doma
14、in modelshow can you integrate them consistently, without overlap or redundancy?The Transfer route: toward learning individual mappings aligning databases directly,Solution: Use a large general-purpose concept network to provide the backgroundthe SENSUS Ontology. Improving alignment by enriching con
15、tent by adding definitional 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 Onto
16、logy: Returning to AI from the Semantic WebMichael Brodie: The Long and Winding Road To Industrial Strength Semantic Web ServicesTim Berners-Lee: SemanticWeb:Where to direct our energy?,15,Jim Hendlers talk,Director of a University of Marylands lab; cochair of the W3C Web Ontology Working Group his
17、research group developed SHOE; creator of DARPAs DAML program“its 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
18、 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 B
19、rodies 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 ! ” fle
20、xible 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.sema
21、nticweb.org/invitedtalks.html,17,Tim Berners-Lees talk,The Semantic Web inventor!,See the conclusions!,Speaking too fast didnt understand anything,18,The main conference,Principal themes Foundations Ontological reasoning Semantic web services Security, trust and privacy Agents and the Semantic Web I
22、nformation 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 Langua
23、ges: RDF(S); OWL Reasoning with DL Web servicescomposition?,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 i
24、n 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 gra
25、ph),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,Fausto Giunchiglia University of Trento C-OWL: Contextualizing Ontologies,Contextual Onto
26、logies = Ontology + context mapping,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-Schne
27、ider University of Manchester RDFS(FA) and RDF MT: two semantics for RDF,24,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 works
28、With 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 clear that RDF(S) is appropriate for both functions (at once) Uniform semantic treatment of triple syntax i.e., “syntax” and “knowledge” triples have s
29、ame semantics Confusing (for some) cyclical meta-model Semantics given by “non-standard” Model Theory,rdfs:Resource instance of rdfs:Class rdfs:Class subclass of rdfs:Resource Resource is instance of its subclass?,Should I use owl:Class or rdfs:Class?,More expressive ontology languages layered on to
30、p 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” Has a First Order/Description Logic style semantics The universe of discourse is divided up into a series of strata User defined facts, vocab
31、ulary and RDF/OWL built-in vocabulary are (typically) in different strata Each modelling primitive belongs to a certain stratum (layer) Labelled with different prefix to indicate the stratum,27,RDFS(FA) layers,Stratum 0 (Instance Layer),Federica, Francesco,Stratum 1 (Ontology Layer),Stratum 2 (Langu
32、age Layer),Stratum 3 (Meta-Language Layer),fa:OResource Person, Researcher workWith ,fa:LResource, fa:LClass fa:LProperty ,fa:MResource, fa:MClass fa:MProperty ,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
33、 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 wit
34、h 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 su
35、ch 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 BPE
36、L (programming lang) to specify the sequence of tasks Partner selected at runtime Automatic semantic translation,D.J.Mandell, S.McIlraith University of Stanformd Adapting BPEL4WS for teh SW: the bottom-up approach to ws interoperation,S.Agarwal, S.Handschuluh, S.Staab University of Karlsruhe Surfing
37、 the Service Web,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 startin
38、g 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,Its the integration!Guideline
39、s Be careful of terms - ontology, semantics, etc Explaining how communities interact Please re-use Dont create new URI schemes Dont re-invent HTTP space Dont re-invent RDF Dont 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,
