Unifying warehoused data with linked open data: A conceptual modeling solution

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Abstract

Linked Open Data (LOD) become one of the most important sources of information allowing enhancing business analyses based on warehoused data with external data. However, Data Warehouses (DWs) do not directly cooperate with LOD datasets due to the differences between data models. In this paper, we describe a conceptual multidimensional model, named Unified Cube, which is generic enough to include both warehoused data and LOD. Unified Cubes provide a comprehensive representation of useful data and, more importantly, support well-informed decisions by including multiple data sources in one analysis. To demonstrate the feasibility of our proposal, we present an implementation framework for building Unified Cubes based on DWs and LOD datasets.

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Ravat, F., & Song, J. (2016). Unifying warehoused data with linked open data: A conceptual modeling solution. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9893 LNCS, pp. 245–259). Springer Verlag. https://doi.org/10.1007/978-3-319-45547-1_20

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