Abstract

From a user perspective, data and services provide a complementary view of an information source: data provide detailed information about specific needs, while services execute processes involving data and returning an informative result as well. For this reason, users need to perform aggregated searches to identify not only relevant data, but also services able to operate on them. At the current state of the art such aggregated search can be only manually performed by expert users, who first identify relevant data, and then identify existing relevant services. In this paper we propose a semantic approach to perform aggregated search of data and services. In particular, we define a technique that, on the basis of an ontological representation of both data and services related to a domain, supports the translation of a data query into a service discovery process. In order to evaluate our approach, we developed a prototype that combines a data integration system with a novel information retrieval-based Web Service discovery engine (XIRE). The results produced by a wide set of experiments show the effectiveness of our approach with respect to IR approaches, especially when Web Service descriptions are expressed by means of a heterogeneous terminology.

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