Data Mediation Support for Triple Space Computing

Triple space computing is an emerging technology for communication and coordination of different semantic technologies. It has been achieved by extending tuple space computing to support RDF as triple space computing. It can play an important role by acting as global middleware providing support for collaboration of different semantic technologies. Several participants from semantic Web and semantic Web services applications, distributed worldwide communicate with each other via triple space due to which the possibility of heterogeneity in the RDF schemas and instances among the communicating participants may arise. In order to resolve this heterogeneity issue, data mediation becomes an important part of the triple space computing architecture. In this paper we introduce data mediation support for triple space computing and further explain how mismatches occur in RDF data, presents an abstract mapping language to specify mapping to cover the heterogeneity, defines architecture of the mediation engine and its interfaces, processing of mediation mapping rules, grounding of mediation rules as RDF triples and finally evaluates with examples