Median Hilal, Christoph Georg Schütz, Michael Schrefl,
"An OLAP Endpoint for RDF Data Analysis Using Analysis Graphs"
: Proc. of the 16th Int. Semantic Web Conference (ISWC 2017) ? Posters and Demonstrations and Industry Tracks co-located with 16th International Semantic Web Conference (ISWC 2017), Oct. 2017, Vienna, Serie CEUR Workshop Proceedings, Vol. 1936, Online at: http://ceur-ws.org/Vol-1963/paper515.pdf, 10-2017
Original Titel:
An OLAP Endpoint for RDF Data Analysis Using Analysis Graphs
Sprache des Titels:
Englisch
Original Buchtitel:
Proc. of the 16th Int. Semantic Web Conference (ISWC 2017) ? Posters and Demonstrations and Industry Tracks co-located with 16th International Semantic Web Conference (ISWC 2017), Oct. 2017, Vienna
Original Kurzfassung:
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
Forschungs-