Ontology-based data sharing in P2P databases

We consider peer-to-peer systems in which peers share structured data through the use of schema mappings. Peers express their queries and rewrite incoming queries on their local schema. We assume the existence of one or more ontologies describing the domain of interest of the peers. The ontologies are used to semantically annotate each peer schema, making explicit the type of information provided by it. A major problem in such a system is that peers cannot easily judge the semantic relativeness of their interests to interests of other peers, as these are expressed by the respective local schemas. Moreover, peers cannot evaluate the semantic relativeness of answers that they receive to their queries. In this paper, we propose a semantic similarity measure for evaluating the semantic relativeness between peer schemas, as well as between queries and their rewritten versions on other peers. The similarity measure is first introduced under the assumption of a shared ontology among the community of peers, and then it is extended, employing ontology matching and translation techniques, to support the comparison of class expressions accross multiple ontologies. The proposed similarity measure adopts the notions of recall and precision from the field of Information Retrieval. Our goal is to use this measure for the identification of semantically relevant peers and the evaluation of the quality of the received answers based on the semantic annotations, the mappings, and the queries issued