The increasing volume and diversity of information in biomedical research is demanding new approaches for data integration in this domain. Semantic Web technologies and applications can leverage the potential of biomedical information integration and discovery, facing the problem of semantic heterogeneity of biomedical information sources. In such an environment, agent technology can assist users in discovering and invoking the services available on the Internet. In this paper we present SEMMAS, an ontology-based, domain-independent framework for seamlessly integrating Intelligent Agents and Semantic Web Services. Our approach is backed with a proof-of-concept implementation where the breakthrough and efficiency of integrating disparate biomedical information sources have been tested.

Service oriented architectures (SOAs) are quickly becoming the defacto solutions for providing end-to-end enterprise connectivity. However realizing the vision of SOA requires, among others, solutions for one fundamental challenge, namely service ranking. Once a set of services that fulfill the requested functionality is discovered, an ordered list of services needs to be created according to users preferences. These preferences are often expressed in terms of multiple non-functional properties (NFPs). This paper proposes a multi-criteria ranking approach for semantic web services. We start by briefly introducing ontological models for NFPs. These models are used to specify rules which describe NFP aspects of services and goals/requests. The ranking mechanism evaluates these NFPs rules using a reasoning engine and produces a ranked list of services according to users preferences.

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