Transforming multidimensional models into OWL-DL ontologies
Résumé
Business intelligence is based on data warehouses. Data warehouses use a multidimensional model, which represents relevant facts and their measures according to different dimensions. Based on this model, OLAP cubes may be defined, enabling decision makers to analyze and synthesize data. Ontologies (and, more specifically, OWL ontologies) are a key component of the semantic Web. This paper proposes an approach to represent multidimensional models as OWL-DL ontologies. To this end, it presents the multidimensional metamodel, the concepts of OWL-DL, and transformation rules for mapping a multidimensional model into and OWL-DL ontology. It then illustrates application to a case study with a simplified example of a spatiotemporal data warehouse. The transformation rules are refined to deal with spatiotemporal data warehouses, applied step by step, and the resulting ontology is implemented in the Protégé ontology tool. As illustrated by the case study, our approach enables better formalization and inferencing, thanks to OWL-DL. The ontology may also be used to represent OLAP cubes on the semantic Web (with RDF), by defining these cubes as instances of the OWL-DL multidimensional ontology.