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Hong Sun, AGFA Healthcare Vincenzo De Florio, Chris Blondia, University of Antwerp, PATS

Implementing a Role Based Mutual Assistance Community with Semantic Service Description and Matching. Hong Sun, AGFA Healthcare Vincenzo De Florio, Chris Blondia, University of Antwerp, PATS. Forecast.

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Hong Sun, AGFA Healthcare Vincenzo De Florio, Chris Blondia, University of Antwerp, PATS

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  1. Implementing a Role Based Mutual Assistance Community with Semantic Service Description and Matching Hong Sun, AGFA Healthcare Vincenzo De Florio, Chris Blondia, University of Antwerp, PATS

  2. Forecast The proportion of elderly people keeps increasing and poses challenges in healthcare in providing cost effective services. Our answer: constructing a role-based mutual assistance community (MAC) to fully utilize the community resources and improve the physical and psychological health of the assisted people. Cornerstone of MAC: Service publication and matchingAn architecture based on semantic service description and matching is presented in this paper. MEDES 2013 30 October, Luxembourg

  3. Outline Role-based MAC: Introduction Semantic service description and matching for MAC Experiments and performance Conclusions MEDES 2013 30 October, Luxembourg

  4. Mutual Assistance Community MEDES 2013 30 October, Luxembourg

  5. Mutual Assistance Community • A community dweller may play different roles • -so as to removes any predefined and artificial distinction between care-givers and care-takers • A community dweller is encouraged to act as service provider • A community dweller is encouraged to participate group activities • Community resources are therefore better utilized MEDES 2013 30 October, Luxembourg

  6. Previous OWL-S Based Implementation MEDES 2013 30 October, Luxembourg

  7. Drawbacks of OWL-S Based Approach • Strict and inflexible format of service expression and matching • The majority of OWL-S matchmakers are based on service inputs/outputs  impossible to match complex services. • Performance penalty in service search/comparison • OWL-S Matcher takes more than 6 seconds to load the profile for service publication, and it takes around 6 seconds to compare two services. • OWLS-MX takes more than 1 second when the service size is around 400. MEDES 2013 30 October, Luxembourg

  8. RDF Graph Based Service Description/Matching • Service description as RDF graph, which is • Flexible in service description • Easy in service management • service publication, update, query, termination • Fast in service matching • Service management/query is coordinated by Fuseki SPARQL server MEDES 2013 30 October, Luxembourg

  9. Basic Ontology @prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#>. @prefix service: <http://www.pats.ua.ac.be/AALService#>. @prefix owl: <http://www.w3.org/2002/07/owl#>. service:Activity a owl:Class. service:ServiceCategory a owl:Class. service:Fitness a owl:Class; rdfs:subClassOf service:ServiceCategory. service:Cycling a owl:Class; rdfs:subClassOf service:Fitness. Service:Walking a owl:Class; rdfs:subClassOf service:Fitness. MEDES 2013 30 October, Luxembourg

  10. Role Based Service Description community dweller role service content service:playRole service:hasScope role service content service:playRole defines the role that a community dwellers plays. service:hasScope defines the scope (service activity) that a role is bond to. MEDES 2013 30 October, Luxembourg

  11. Inference It enables to match services which are syntactically different, but semantically close. It is executed by EYE Reasoning Engine. Ref: EYE engine: http://eulersharp.sourceforge.net/ <…/Activity/101> service:hasServiceCategoryservice:Jogging. infer <…/Activity/101> service:hasInferredServiceCategoryservice:Fitness. MEDES 2013 30 October, Luxembourg

  12. Architecture MEDES 2013 30 October, Luxembourg

  13. Workflow MEDES 2013 30 October, Luxembourg

  14. Service Query It is possible to filter on different properties; the service match process is therefore much more flexible compared with our previous implementation. MEDES 2013 30 October, Luxembourg

  15. Service Publication and Termination Service Termination Service Publication MEDES 2013 30 October, Luxembourg

  16. Performance A set of sample activity graphs that defines a different number of activities are randomly generated. Different threads of service queries are tested as well. MEDES 2013 30 October, Luxembourg

  17. …Every new solution breeds new problems… MAC basic assumption: every new service needs to be matched with known services  scalability Upper bound on community size (heap space exception) Current solution: breaking down the communities into sub-communities Fractal organization MEDES 2013 30 October, Luxembourg

  18. Conclusion RDF graph based implementation outperforms our previous OWL-S based implementation in: • Flexibility in service description. • Ease in service management. • Speed in service matching. Future work: 1) semantic service composition 2) automate the workflow 3) fractal social organizations http://www.youtube.com/watch?v=HKU7gOI57e0 Semantic service description & matching framework for MAC MEDES 2013 30 October, Luxembourg

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