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Towards a Knowledge-Based Approach to Semantic Service Composition

Biomedical Sciences Research Institute Computer Science Research Institute Environmental Sciences Research Institute Nanotechnology & Advanced Materials Research Institute

Chen, Liming, Shadbolt, Nigel R., Goble, Carole, Tao, Feng, Cox, Simon and Smart , Paul (2003) Towards a Knowledge-Based Approach to Semantic Service Composition. In: The SemanticWeb - ISWC 2003. Springer Berlin / Heidelberg, pp. 319-334. ISBN 978-3-540-20362-9 [Book section]

Full text not available from this repository.

DOI: 10.1007/b14287

Abstract

The successful application of Grid and Web Service technologies to real-world problems, such as e-Science [1], requires not only the development of a common vocabulary and meta-data framework as the basis for inter-agent communication and service integration but also the access and use of a rich repository of domain-specific knowledge for problem solving. Both requirements are met by the respective outcomes of ontological and knowledge engineering initiatives. In this paper we discuss a novel, knowledge-based approach to resource synthesis (service composition), which draws on the functionality of semantic web services to represent and expose available resources. The approach we use exploits domain knowledge to guide the service composition process and provide advice on service selection and instantiation. The approach has been implemented in a prototype workflow construction environment that supports the runtime recommendation of a service solution, service discovery via semantic service descriptions, and knowledge-based configuration of selected services. The use of knowledge provides a basis for full automation of service composition via conventional planning algorithms. Workflows produced by this system can be executed through a domain-specific direct mapping mechanism or via a more fluid approach such as WSDL-based service grounding. The approach and prototype have been used to demonstrate practical benefits in the context of the Geodise initiative [2].

Item Type:Book section
Faculties and Schools:Faculty of Computing & Engineering
Faculty of Computing & Engineering > School of Computing and Mathematics
Research Institutes and Groups:Computer Science Research Institute
Computer Science Research Institute > Smart Environments
ID Code:11669
Deposited By:Dr Liming Chen
Deposited On:09 Mar 2010 15:52
Last Modified:09 Mar 2010 15:52

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