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Dietze Aswc 2009 Final

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  • 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.
    • Semantic Web Services (SWS) mediation
    • Two-fold matchmaking approach for SWS
    • Prototypical implementation & application
    • Conclusions
    Outline
  • 3. Introduction Semantic Web Services (SWS)
      • Formalisations of Web services in terms of capabilities (Cap) , interfaces (If) and non-functional properties (Nfp)
      • Capabilities: assumptions (Ass) and effects (Eff)
      • Use ontologies O (i.e. tuple of concepts C , instances I , properties P , relations R and axioms A)
      • Reference models e.g. OWL-S, WSMO, SAWSDL
    sws:WebService SWS.2 sws:WebService SWS.3 sws:WebService SWS.1 WebService WS.2 WebService WS.3 WebService WS.1
  • 4.
    • SWS discovery: matchmaking of capabilities of SWS e.g. :
    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.
    • SWS discovery: matchmaking of capabilities of SWS e.g. :
    • I.e., matching logical expressions
    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.
    • SWS discovery: matchmaking of capabilities of SWS e.g. :
    • I.e., matching logical expressions…
    • … which are heterogeneous.
    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.
    • SWS discovery: matchmaking of capabilities of SWS e.g. :
    • I.e., matching logical expressions…
    • … which are heterogeneous.
    • Requires: mediation between concepts/instances across heterogeneous SWS.
    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.
    • Proposal:
      • SWS matchmaking as two-fold process
        • Semantic mediation via ontology (instance) mapping
        • Logical reasoning for matchmaking of capability/interface descriptions
    SWS matchmaking Two-fold process
  • 9.
    • Proposal:
      • SWS matchmaking as two-fold process
        • Semantic mediation via ontology (instance) mapping
        • Logical reasoning for matchmaking of capability/interface descriptions
    • Issues:
      • Traditional SWS matchmaking focusses on (ii)
      • Integration of (i):
        • Via manual mappings? - costly
        • Via exploitation of linguistic or structural similarities? - prone to errors
      • Representations allowing for implicit similarity-computation ?
    SWS matchmaking Two-fold process
  • 10.
      • Refining SWS ontologies through multiple “Mediation Spaces” (MS), i.e. multidimensional, vector spaces
      • Through MS ontology (extends SWS descriptions)
      • Concept C in SWS ontology O => Mediation Space MS / Instance I of C => member M (vector) in MS
    Semantic-level mediation Approach: instance similarity computation in shared MS
  • 11.
      • Similarity-computation between SWS instances => spatial distances in MS
      • e.g. Euclidean distance:
      • Common agreement at schema (i.e. MS) level
    Semantic-level mediation Approach: instance similarity computation in shared MS
  • 12. Similarity-based service matchmaking Implementation based on WSMO/IRS-III
    • Implementation: Web Service Modelling Ontology (WSMO) & SWS environment IRS-III
  • 13. Similarity-based service matchmaking Implementation based on WSMO/IRS-III
    • Implementation: Web Service Modelling Ontology (WSMO) & SWS environment IRS-III
    • WSMO Mediator: computation of similarities between given request (WSMO Goal, G 1 ) and set of x associated SWS ( SWS 1 ..SWS x ):
    • Limitation: suitability of service computed based on instance similarities (=> current work: integration into “real” two-fold matchmaking)
  • 14.
    • Uses representational approach (MS, similarity-based WSMO Mediator)
    • Retrieval of distributed video resources (provided within EU FP7 IP NoTube - http://notube.tv)
    • Keyword-based searches across Web services exposing video repositories
      • BBC Backstage (news feed) [ http:// backstage.bbc.co.uk / ]
      • BBC Programmes RDF [ http://api.talis.com/stores/bbc-backstage ]
      • Open Video [ http://www.open-video.org / ]
      • OU channel on YouTube [ http://www.youtube.com/ou ]
      • YouTube (mobile feed) [ http://www.youtube.com/ou ]
    • Similarity-based service discovery for given request
    Semantic mediation through MS Prototypical application
  • 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. 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. 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. 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
    • Requests (WSMO Goals) via AJAX-based UI
    • Consist of:
      • Input parameters: set of keywords
      • Assumption: defined through dynamically created instances (based on measurements describing purpose and environment)
    • Similarity-based SWS discovery based on WSMO mediator
  • 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.
    • Summary:
      • Two-fold approach: considering semantic-level mediation as implicit element of SWS matchmaking
      • Mediation approach based on (instance) similarity-computation
    • Issues:
      • Matchmaking purely based on instance similarities (=> current work: integration into “real” two-fold matchmaking)
      • Similarity-calculation requires overlapping MS and measurable quality dimensions
      • Additional representational effort => future work: evaluation
    Conclusions Summary & discussion
  • 21. Thank you!
    • E-mail: [email_address]
    • Web: http://people.kmi.open.ac.uk/dietze

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