SomeWhere: a scalable peer-to-peer infrastructure for querying distributed ontologies

In this invited talk, we present the SomeWhere approach and infrastructure for building semantic peer-to-peer data management systems based on simple personalized ontologies distributed at a large scale Somewhere is based on a simple class-based data model in which the data is a set of resource identifiers (e.g., URIs), the schemas are (simple) definitions of classes possibly constrained by inclusion, disjunction or equivalence statements, and mappings are inclusion, disjunction or equivalence statements between classes of different peer ontologies In this setting, query answering over peers can be done by distributed query rewriting, which can be equivalently reduced to distributed consequence finding in propositional logic It is done by using the message-passing distributed algorithm that we have implemented for consequence finding of a clause w.r.t a set of distributed propositional theories We summarize its main properties (soundness, completeness and termination), and we report experiments showing that it already scales up to a thousand of peers Finally, we mention ongoing work on extending the current data model to RDF(S) and on handling possible inconsistencies between the ontologies of different peers.