In the context of exploratory OLAP, coupling the information wealth of linked data with the precision and detail of corporate data can greatly improve the effectiveness of the decision-making process. In this paper we outline an approach that enables users to extend the hierarchies in their corporate cubes through a user-guided process that explores selected linked data and derives hierarchies from them. This is done by identifying in the linked data the recurring modeling patterns that express roll-up relationships between RDF concepts and translating them into multidimensional knowledge.

Peer Reviewed