Populating Data Warehouses with Semantic Data

The Semantic Web has become a new environment that enables organizations to attach semantic annotations taken from domain and application ontologies to the information they generate. As a result, large amounts of complex, semi-structured and heterogeneus semantic data repositories are being made available. In this paper, we present an automatic method for on-demand construction of fact tables aimed at analyzing semantic data expressed as instance stores in RDF/OWL. The starting point of the method is a multidimensional star schema (i.e. topic of analysis, dimensions and measures) designed by the analyst by picking up concepts and properties from the ontology of the instance store. The method exploits the underlying semantics of ontology axioms in order to derive facts, that is, “valid combinations” of instances and literals that fulfill the analyst needs. Moreover, both the ontology axioms and the instances are indexed in order to reach scalability. We have tested the method with a synthetically generated instance set in order to show its scalability and effectiveness.