Mediation Spaces for Similarity-Based Semantic Web Services Selection

Abstract

Semantic Web Services (SWS) aim at the automated discovery, selection and orchestration of Web services based on comprehensive, machine-interpretable semantic descriptions. The latter are, in principle, deployed by multiple possible actors (i.e., service providers and service consumers); thus, a high level of heterogeneity between distinct SWS annotations is expected. Therefore, mediation between concurrent semantic representations of services is a key requirement to fully implement the SWS vision. In this paper, the authors argue that “semantic-level mediation” is necessary to identify semantic similarities across distinct SWS representations. The authors formalize and implement a mediation approach based on “Mediation Spaces” (MS), which enables the implicit representation of semantic similarities among distinct SWS descriptions. As a result, given a specific SWS approach and the proposed MS, a general purpose algorithm is implemented to empower SWS selection with the automatic computation of semantic similarities between a given SWS request and a set of SWS offers. A prototypical application illustrates the approach and highlights the benefits w.r.t. current mediation approaches.