Towards Ontology-Driven RDF Analytics

B. Neumayr, C. Schütz, M. Schrefl
Neum15a (2015)
Advances in Conceptual Modeling, Proceedings ER 2015 Workshops, AHA, CMS, EMoV, MoBiD, MORE-BI, MReBA, QMMQ, and {SCME}, Ed.: Manfred A. Jeusfeld, Kamalakar Karlapalem, Stockholm, Sweden, October 19-22, 2015, Springer Verlag, Lecture Notes in Computer Science (LNCS Vol. 9382), ISBN 978-3-319-25746-4, pp. 210-219, 2015.
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Abstract (English)

The RDF data model lends itself to the organization of graph-structured data. The analysis of such data requires specific tools and techniques broadly summarized as RDF analytics. In particular, traditional approaches to the aggregation of multidimensional data do not apply directly to RDF data due to the lack of information regarding the granularity level of the data and unclear semantics of aggregation. Ontologies, however, may provide the additional information required for RDF data aggregation. Using a vocabulary for ontology-based RDF analytics in conjunction with existing domain ontologies, modelers may declaratively specify aggregated views over RDF data. In this paper we describe the fundamentals of ontology-driven RDF analytics based on RDF, RDF Schema, and SPARQL. We present a proof-of-concept implementation of the basic approach that uses open-source technology, thereby demonstrating feasibility. We further discuss possible future extensions to the basic approach.

Keywords: Business intelligence – Semantic web – SPARQL