Unifying Warehoused Data with Linked Open Data: A Conceptual Modeling Solution

Franck Ravat (1, 2) , Jiefu Song (1)

1 IRIT-SIG - Systèmes d’Informations Généralisées
2 UT Capitole - Université Toulouse Capitole

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.

Mots clés: Data warehouse; Linked open data; Unified conceptual model

Domaines: Théorie de l'information [cs.IT]; Recherche d'information [cs.IR]

Franck Ravat, Jiefu Song. Unifying Warehoused Data with Linked Open Data: A Conceptual Modeling Solution. 6th International Conference Model and Data Engineering (MEDI 2016), Sep 2016, Almeria, Spain. pp. 245-259. ⟨hal-01484964⟩