Data Access over Large Semi - Structured Databases

Ontology-Based Data Access is a problem aiming at answering conjunctive queries over facts enriched by ontological information. There are today two manners of encoding such ontological content: Description Logics and rule-bases languages. The emergence of very large knowledge bases, often with unstructured information has provided an additional challenge to the problem. In this work, we will study the elementary operations needed in order to set up the storage and querying foundations of a rule-based reasoning system. The study of different storage solutions have led us to develop ALASKA, a generic and logicbased architecture regrouping different storage methods and enabling one to write reasoning programs generically. This paper features the design and construction of such architecture, and the use of it in order to verify the efficiency of storage methods for the key operations for RBDA, storage on disk and entailment computing.