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Superimposed Multidimensional Schemas for RDF Data Analysis

Authors: M. Hilal, C. Schütz, M. Schrefl
Paper: Hila17b (2017)
Citation: Proceedings of the IEEE 14th International Scientific Conference on Informatics (Informatics 2017), November 14–16, 2017, Poprad, Slovakia, 7 pages, 2017.
Resources: Copy  (In order to obtain the copy please send an email with subject  Hila17b  to dke.win@jku.at)


Abstract (English):

Traditional data analysis employs online analytical processing (OLAP) systems operating on multidimensional (MD) data. The Resource Description Framework (RDF) serves as the foundation for the publication of a growing amount of semantic web data still largely untapped by data analysis. RDF data, however, do not typically follow an MD structure and, therefore, elude traditional OLAP. We propose an approach for superimposing MD structures over arbitrary RDF datasets. On top of that, we present a high-level querying mechanism to express MD queries, which can be automatically translated into SPARQL queries over the source data. As a consequence, data analysts that are unfamiliar with SPARQL, may still incorporate RDF data sources into the analysis. Superimposed MD schemas also serve as foundation for Semantic Web Analysis Graphs which capture analysis processes for increased self-service capabilities.

Keywords: Business Intelligence, Data Warehouse, Semantic Technologies, Linked Data