Towards Adaptive and Semantic Database Model for RDF Data Stores

RDF Schema is a basic and yet very important language for specifying ontologies in the context of Semantic Web. Ontologies can be used to obtain more information from that explicitly stated. Traditionally, the process of revealing implicit knowledge, known as inference or reasoning, is realised by a reasoner -- a component which either processes data to infer all conclusions in advance or, given a query, infers all implicit answers during a query evaluation process. In this paper, we present an alternative approach based on structuring data in a database according to underlying ontologies. This knowledge structure is employed for directing query evaluation to data relevant for the given query. Thus, this method reduces reasoning to retrieving. We show that the proposed schema preserves the semantics of RDF and RDFS in standard use cases.