Mediation spaces for similarity-based semantic web services selection

Semantic Web Services (SWS) aim at the automated discovery, selection and orchestration of Web services on the basis of comprehensive, machine-interpretable semantic descriptions. However, heterogeneities between distinct SWS representations pose strong limitations w.r.t. interoperability and reusability. Hence, semantic-level mediation, i.e. mediation between concurrent semantic representations of services, is a key requirement to allow SWS matchmaking algorithms to compare capabilities of distinct SWS. In that, semantic-level mediation requires to identify similarities across distinct SWS representations. Since current approaches to mediate between distinct service annotations rely either on manual one-to-one mappings or on semiautomatic mappings based on the exploitation of linguistic or structural similarities, these are perceived to be costly and error-prone. We propose a mediation approach enabling the implicit representation of similarities across distinct SWS by grounding these in so-called Mediation Spaces (MS). Given a set of SWS and their respective MS grounding, a general-purpose mediator automatically computes similarities to identify the most appropriate SWS for a given request. A prototypical application illustrates our approach