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. MEDES 2013 30 October, Luxembourg
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 matching An architecture based on semantic service description and matching is presented in this paper.
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3. MEDES 2013 30 October, Luxembourg
Outline
Role-based MAC: Introduction
Semantic service description and matching for MAC
Experiments and performance
Conclusions
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4. Mutual Assistance Community
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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
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6. Previous OWL-S Based Implementation
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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.
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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
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Basic Ontology
@prefix rdfs: <
@prefix service: <
@prefix 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.
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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.
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11. MEDES 2013 30 October, Luxembourg
Inference
It enables to match services which are syntactically different, but semantically close. It is executed by EYE Reasoning Engine.
Ref: EYE engine:
<…/Activity/101> service:hasServiceCategory service:Jogging.
infer
<…/Activity/101> service:hasInferredServiceCategory service:Fitness.
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12. MEDES 2013 30 October, Luxembourg
Architecture
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Workflow
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Service Query
It is possible to filter on different properties; the service match process is therefore much more flexible compared with our previous implementation.
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15. Service Publication and Termination
Service Termination
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16. MEDES 2013 30 October, Luxembourg
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.
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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
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18. MEDES 2013 30 October, Luxembourg
Conclusion
Semantic service description & matching framework for MAC
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
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