1. Service discovery with semantic alignment Alberto Fernández AT COST WG1 meeting, Cyprus, 15-16 Dec, 2009

2. Introduction Service coordination in open environments  Identification of functionality (service) required  Service provider discovery  Service provider selection (trust, reputation, QoS)  Service engagement (negotiation)  Service invocation Agreement Technologies for Service coordination  Semantics, negotiation, trust, …

3. Service Provider Discovery Matching service advertisements against service requests  Service description languages  Usually identical for advertisements and request

4. OWL-S service profile example INPUTS OUTPUTS CATEGORIES PARAMETERS EFFECTS/PRECONDITIONS Ontology

5. Service Provider Discovery Semantic Mismatches  Service description models  Domain ontologies

6. Architecture service description service request Model Alignment service description service request Service Matching Degree of match dom(C 1,C 2 ) Local Alignment KB Local Alignment KB Service Directory Service Directory Semantic Concept Matching Concept Alignment Registry Alignment Registry Different ontologies OWLS, WSMO, SAWSDL, WSDL, keywords, text,…

7. Service Model Alignment Service Description Approaches  Semantic: OWL-S, WSMO  Syntactic: WSDL  Hybrid: SAWSDL  Light models: keywords, tag-clouds, textual Common models for pairs of SD models  Possible loss of expressiveness Integrated model for service discovery  Union of common models

8. Integrated model for service matchmaking

9. ElementOWL-SWSMOSAWSDLWSDL Keyword (tag) Tag Cloud Text input xxxx--- output xxxx--- precondition xx----- effect xx----- keywords ---- x -- text xx----x category xxx- -- - tag cloud ----- x -

10. Integrated model for service matchmaking ElementOWL-SWSMOSAWSDLWSDL Keyword (tag) Tag Cloud Text input xxxx--- output xxxx--- precondition xx----- effect xx----- keywords O sem O syn x text xxO sem O syn x category xxxO syn -- - tag cloud O sem O syn x

11. Architecture service description service request Model Alignment service description service request Service Matching Degree of match dom(C 1,C 2 ) Local Alignment KB Local Alignment KB Service Directory Service Directory Semantic Concept Matching Concept Alignment Registry Alignment Registry

12. Service Matching Aggregation over matching of individual concepts (only for common fields) Current approaches to Semantic IOPE  I A  I R  O R  O A  P A  P R  E R  E A

13. Semantic Concept Matching Degree of Match between C A and C R. Combination of  Level of Match subsumption relation Exact, plugin, subsumes, fail, …  Concept Similarity Semantic distance

14. Semantic Concept Matching vehicle carvantruckbus Japanese car hondamazdanissantoyota American car chevydodgeford searched found plug-in levels of match

15. Semantic Concept Matching vehicle carvantruckbus Japanese car hondamazdanissantoyota American car chevydodgeford found searched subsumes levels of match exact > plug-in > subsumes > fail

16. Semantic Concept Matching vehicle carvantruckbus Japanese car hondamazdanissantoyota American car chevydodgeford distance = 2 concept similarity

17. Service Matching Non IOPEs (keywords, tag clouds, categories)  Syntactic:  Semantic:

18. Concept Alignment Alignments (or mappings) between two ontologies O and O’: where:  e and e’ are the entities considered  n: is a degree of trust (confidence)  R is the relation holding between e and e’. Representation in RDF SPARQL for querying

19. Open Issues SPARQL as query language Two stage discovery process  e.g. the requester doesn't know the inputs required Matchmaking completely in the directory?  Private information Scalability  Distributed directories  Ontology alignments discovery

20. Conclusions Summary  Architecture for service discovery  Semantic alignment  Common model for service descriptions Future work  Implementation (currently) and evaluation  Open issues pointed out

21. Service discovery with semantic alignment Alberto Fernández AT COST WG1 meeting, Cyprus, 15-16 Dec, 2009