Dietze Aswc 2009 Final

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Dietze Aswc 2009 Final

  1. 1. Two-Fold Service Matchmaking – Applying Ontology Mapping for Semantic Web Service Discovery /// ASWC’09, Shanghai, China, December 08, 2009 Stefan Dietze 1 , Neil Benn 1 , John Domingue 1 , Alex Conconi 2 , Fabio Cattatoni 2 1 Knowledge Media Institute, The Open University, UK 2 TXT eSolutions, Italy
  2. 2. <ul><li>Semantic Web Services (SWS) mediation </li></ul><ul><li>Two-fold matchmaking approach for SWS </li></ul><ul><li>Prototypical implementation & application </li></ul><ul><li>Conclusions </li></ul>Outline
  3. 3. Introduction Semantic Web Services (SWS) <ul><ul><li>Formalisations of Web services in terms of capabilities (Cap) , interfaces (If) and non-functional properties (Nfp) </li></ul></ul><ul><ul><li>Capabilities: assumptions (Ass) and effects (Eff) </li></ul></ul><ul><ul><li>Use ontologies O (i.e. tuple of concepts C , instances I , properties P , relations R and axioms A) </li></ul></ul><ul><ul><li>Reference models e.g. OWL-S, WSMO, SAWSDL </li></ul></ul>sws:WebService SWS.2 sws:WebService SWS.3 sws:WebService SWS.1 WebService WS.2 WebService WS.3 WebService WS.1
  4. 4. <ul><li>SWS discovery: matchmaking of capabilities of SWS e.g. : </li></ul>SWS matchmaking Issues sws:WebService SWS.2 sws:WebService SWS.3 sws:Request R.1 sws:WebService SWS.1 WebService WS.2 WebService WS.3 WebService WS.1 ? ?
  5. 5. <ul><li>SWS discovery: matchmaking of capabilities of SWS e.g. : </li></ul><ul><li>I.e., matching logical expressions </li></ul>SWS matchmaking Issues sws:WebService SWS.2 sws:WebService SWS.3 sws:Request R.1 sws:WebService SWS.1 WebService WS.2 WebService WS.3 WebService WS.1 has-assumption has-assumption
  6. 6. <ul><li>SWS discovery: matchmaking of capabilities of SWS e.g. : </li></ul><ul><li>I.e., matching logical expressions… </li></ul><ul><li>… which are heterogeneous. </li></ul>SWS matchmaking Issues sws:WebService SWS.2 sws:WebService SWS.3 sws:Request R.1 sws:WebService SWS.1 WebService WS.2 WebService WS.3 WebService WS.1 ? <Location rdf:ID=&quot;Milton_Keynes&quot;/> <geospatialLocation rdf:ID=&quot;M-K&quot;/> has-assumption has-assumption
  7. 7. <ul><li>SWS discovery: matchmaking of capabilities of SWS e.g. : </li></ul><ul><li>I.e., matching logical expressions… </li></ul><ul><li>… which are heterogeneous. </li></ul><ul><li>Requires: mediation between concepts/instances across heterogeneous SWS. </li></ul>SWS matchmaking Semantic-level mediation sws:WebService SWS.2 sws:WebService SWS.3 sws:Request R.1 sws:WebService SWS.1 WebService WS.2 WebService WS.3 WebService WS.1 Semantic-Level Mediation Mediation between heterogeneous semantic representations
  8. 8. <ul><li>Proposal: </li></ul><ul><ul><li>SWS matchmaking as two-fold process </li></ul></ul><ul><ul><ul><li>Semantic mediation via ontology (instance) mapping </li></ul></ul></ul><ul><ul><ul><li>Logical reasoning for matchmaking of capability/interface descriptions </li></ul></ul></ul>SWS matchmaking Two-fold process
  9. 9. <ul><li>Proposal: </li></ul><ul><ul><li>SWS matchmaking as two-fold process </li></ul></ul><ul><ul><ul><li>Semantic mediation via ontology (instance) mapping </li></ul></ul></ul><ul><ul><ul><li>Logical reasoning for matchmaking of capability/interface descriptions </li></ul></ul></ul><ul><li>Issues: </li></ul><ul><ul><li>Traditional SWS matchmaking focusses on (ii) </li></ul></ul><ul><ul><li>Integration of (i): </li></ul></ul><ul><ul><ul><li>Via manual mappings? - costly </li></ul></ul></ul><ul><ul><ul><li>Via exploitation of linguistic or structural similarities? - prone to errors </li></ul></ul></ul><ul><ul><li>Representations allowing for implicit similarity-computation ? </li></ul></ul>SWS matchmaking Two-fold process
  10. 10. <ul><ul><li>Refining SWS ontologies through multiple “Mediation Spaces” (MS), i.e. multidimensional, vector spaces </li></ul></ul><ul><ul><li>Through MS ontology (extends SWS descriptions) </li></ul></ul><ul><ul><li>Concept C in SWS ontology O => Mediation Space MS / Instance I of C => member M (vector) in MS </li></ul></ul>Semantic-level mediation Approach: instance similarity computation in shared MS
  11. 11. <ul><ul><li>Similarity-computation between SWS instances => spatial distances in MS </li></ul></ul><ul><ul><li>e.g. Euclidean distance: </li></ul></ul><ul><ul><li>Common agreement at schema (i.e. MS) level </li></ul></ul>Semantic-level mediation Approach: instance similarity computation in shared MS
  12. 12. Similarity-based service matchmaking Implementation based on WSMO/IRS-III <ul><li>Implementation: Web Service Modelling Ontology (WSMO) & SWS environment IRS-III </li></ul>
  13. 13. Similarity-based service matchmaking Implementation based on WSMO/IRS-III <ul><li>Implementation: Web Service Modelling Ontology (WSMO) & SWS environment IRS-III </li></ul><ul><li>WSMO Mediator: computation of similarities between given request (WSMO Goal, G 1 ) and set of x associated SWS ( SWS 1 ..SWS x ): </li></ul><ul><li>Limitation: suitability of service computed based on instance similarities (=> current work: integration into “real” two-fold matchmaking) </li></ul>
  14. 14. <ul><li>Uses representational approach (MS, similarity-based WSMO Mediator) </li></ul><ul><li>Retrieval of distributed video resources (provided within EU FP7 IP NoTube - http://notube.tv) </li></ul><ul><li>Keyword-based searches across Web services exposing video repositories </li></ul><ul><ul><li>BBC Backstage (news feed) [ http:// backstage.bbc.co.uk / ] </li></ul></ul><ul><ul><li>BBC Programmes RDF [ http://api.talis.com/stores/bbc-backstage ] </li></ul></ul><ul><ul><li>Open Video [ http://www.open-video.org / ] </li></ul></ul><ul><ul><li>OU channel on YouTube [ http://www.youtube.com/ou ] </li></ul></ul><ul><ul><li>YouTube (mobile feed) [ http://www.youtube.com/ou ] </li></ul></ul><ul><li>Similarity-based service discovery for given request </li></ul>Semantic mediation through MS Prototypical application
  15. 15. Semantic mediation through MS Prototypical application SWS 1 : OU-youtube O 1 :Purp O 1 :Env SWS 2 : bbc-programmes O 2 :Purp O 2 :Env SWS 3 : open-video O 3 :Purp O 3 :Env SWS 4 : bbc-backstage O 4 :Purp O 4 :Env M 6 2 ={v 1 , v 2 } SWS 5 : mobile-youtube O 5 :Purp O 5 :Env MS 2 Environment Space MS 1 Purpose Space SWS 6 : get-video-request M 6 1 ={v 1, v 2 , v 3 } WS 1 : OU-youtube WS 2 : bbc-programmes WS 3 : open-video WS 4 : bbc-backstage WS 5 : mobile-youtube
  16. 16. Semantic mediation through MS Prototypical application SWS 1 : OU-youtube O 1 :Purp O 1 :Env SWS 2 : bbc-programmes O 2 :Purp O 2 :Env SWS 3 : open-video O 3 :Purp O 3 :Env SWS 4 : bbc-backstage O 4 :Purp O 4 :Env M 6 2 ={v 1 , v 2 } SWS 5 : mobile-youtube O 5 :Purp O 5 :Env MS 2 Environment Space MS 1 Purpose Space SWS 6 : get-video-request M 6 1 ={v 1, v 2 , v 3 } WS 1 : OU-youtube WS 2 : bbc-programmes WS 3 : open-video WS 4 : bbc-backstage WS 5 : mobile-youtube
  17. 17. Semantic mediation through MS Prototypical application SWS 1 : OU-youtube O 1 :Purp O 1 :Env SWS 2 : bbc-programmes O 2 :Purp O 2 :Env SWS 3 : open-video O 3 :Purp O 3 :Env SWS 4 : bbc-backstage O 4 :Purp O 4 :Env M 6 2 ={v 1 , v 2 } SWS 5 : mobile-youtube O 5 :Purp O 5 :Env MS 2 Environment Space MS 1 Purpose Space SWS 6 : get-video-request M 6 1 ={v 1, v 2 , v 3 } WS 1 : OU-youtube WS 2 : bbc-programmes WS 3 : open-video WS 4 : bbc-backstage WS 5 : mobile-youtube {(p 1 *information, p 2 *education, p 3 *leisure)} = CS 1 {(p 4 *resolution, p 5 *bandwidth)} = CS 2
  18. 18. Semantic mediation through MS Prototypical application SWS 1 : OU-youtube O 1 :Purp O 1 :Env SWS 2 : entertain-youtube O 2 :Purp O 2 :Env SWS 3 : open-video O 3 :Purp O 3 :Env SWS 4 : bbc-backstage O 4 :Purp O 4 :Env M 6 2 ={v 1 , v 2 } SWS 5 : mobile-youtube O 5 :Purp O 5 :Env MS 2 Environment Space MS 1 Purpose Space SWS 6 : get-video-request M 6 1 ={v 1, v 2 , v 3 } WS 1 : OU-youtube WS 2 : entertain-youtube WS 3 : open-video WS 4 : bbc-backstage WS 5 : mobile-youtube <ul><li>Requests (WSMO Goals) via AJAX-based UI </li></ul><ul><li>Consist of: </li></ul><ul><ul><li>Input parameters: set of keywords </li></ul></ul><ul><ul><li>Assumption: defined through dynamically created instances (based on measurements describing purpose and environment) </li></ul></ul><ul><li>Similarity-based SWS discovery based on WSMO mediator </li></ul>
  19. 19. Demo SWS 1 : OU-youtube O 1 :Purp O 1 :Env SWS 2 : entertain-youtube O 2 :Purp O 2 :Env SWS 3 : open-video O 3 :Purp O 3 :Env SWS 4 : bbc-backstage O 4 :Purp O 4 :Env M 6 2 ={v 1 , v 2 } SWS 5 : mobile-youtube O 5 :Purp O 5 :Env MS 2 Environment Space MS 1 Purpose Space SWS 6 : get-video-request M 6 1 ={v 1, v 2 , v 3 } WS 1 : OU-youtube WS 2 : entertain-youtube WS 3 : open-video WS 4 : bbc-backstage WS 5 : mobile-youtube
  20. 20. <ul><li>Summary: </li></ul><ul><ul><li>Two-fold approach: considering semantic-level mediation as implicit element of SWS matchmaking </li></ul></ul><ul><ul><li>Mediation approach based on (instance) similarity-computation </li></ul></ul><ul><li>Issues: </li></ul><ul><ul><li>Matchmaking purely based on instance similarities (=> current work: integration into “real” two-fold matchmaking) </li></ul></ul><ul><ul><li>Similarity-calculation requires overlapping MS and measurable quality dimensions </li></ul></ul><ul><ul><li>Additional representational effort => future work: evaluation </li></ul></ul>Conclusions Summary & discussion
  21. 21. Thank you! <ul><li>E-mail: [email_address] </li></ul><ul><li>Web: http://people.kmi.open.ac.uk/dietze </li></ul>

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