Unifying Warehoused Data with Linked Open Data: A Conceptual Modeling Solution [chapter]

Franck Ravat, Jiefu Song
<span title="">2016</span> <i title="Springer International Publishing"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/2w3awgokqne6te4nvlofavy5a4" style="color: black;">Lecture Notes in Computer Science</a> </i> &nbsp;
OATAO is an open access repository that collects the work of Toulouse researchers and makes it freely available over the web where possible. This is an author-deposited version published in : http://oatao.univ-toulouse.fr/ Eprints ID : 17173 The contribution was presented at MEDI 2016 : 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
more &raquo; ... ectly 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.
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/978-3-319-45547-1_20">doi:10.1007/978-3-319-45547-1_20</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/kwky3ov65jfixcawtxhsdb35wy">fatcat:kwky3ov65jfixcawtxhsdb35wy</a> </span>
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