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An OLAP Endpoint for RDF Data Analysis Using Analysis Graphs

Authors: M. Hilal, C. Schütz, M. Schrefl
Paper: Hila17a (2017)
Citation: Proceedings of the 16th International Semantic Web Conference (ISWC 2017) – Posters and Demonstrations and Industry Tracks co-located with 16th International Semantic Web Conference (ISWC 2017), October 23rd - 25th, 2017, Vienna, Austria, CEUR Workshop Proceedings, Vol. 1963, Online at: http://ceur-ws.org/Vol-1963/paper515.pdf, open access, peer reviewed, 2017.
Resources: Copy  (In order to obtain the copy please send an email with subject  Hila17a  to dke.win@jku.at)


Abstract (English):

Exploiting Resource Description Framework (RDF) data for Online Analytical Processing (OLAP), especially Linked Open Data (LOD), could allow analysts to obtain interesting insights. To conduct OLAP analysis over RDF data, analysts should know the specific semantics, structure, and querying mechanisms of such data. Furthermore, these data should ideally adhere to a multidimensional structure to be accessible to OLAP. In this demo paper, we present an OLAP endpoint that allows casual analysts to perform self-service OLAP analysis over RDF datasets. Specifically, analysts can instantiate semantic web analysis graphs, which are predefined models of the analysis processes. Semantic web analysis graphs are built on top of multidimensional structures that can be superimposed over arbitrary RDF datasets.

Keywords: Linked Open Data, Multidimensional Model, Self-Service Business Intelligence