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.

Towards Exploratory OLAP on Linked Data

RIZZI, STEFANO;GALLINUCCI, ENRICO;GOLFARELLI, MATTEO;
2016

Abstract

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.
Proceedings 24th Italian Symposium on Advanced Database Systems
86
93
Rizzi, Stefano; Gallinucci, Enrico; Golfarelli, Matteo; Abelló, Alberto; Romero, Oscar
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/543998
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