Towards Ontology-Driven RDF Analytics

  • Bernd NeumayrEmail author
  • Christoph G. Schuetz
  • Michael Schrefl
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9382)


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.


Business intelligence Semantic web SPARQL 


  1. 1.
    Anderlik, S., Neumayr, B., Schrefl, M.: Using domain ontologies as semantic dimensions in data warehouses. In: Atzeni, P., Cheung, D., Ram, S. (eds.) ER 2012 Main Conference 2012. LNCS, vol. 7532, pp. 88–101. Springer, Heidelberg (2012) CrossRefGoogle Scholar
  2. 2.
    Colazzo, D., Goasdoué, F., Manolescu, I., Roatis, A.: RDF analytics: lenses over semantic graphs. In: Proceedings of the 23rd International World Wide Web Conference, WWW 2014, pp. 467–478 (2014)Google Scholar
  3. 3.
    Kaoudi, Z., Manolescu, I.: RDF in the clouds: a survey. VLDB J. 24(1), 67–91 (2015)CrossRefGoogle Scholar
  4. 4.
    Motik, B.: On the properties of metamodeling in OWL. J. Logic Comput. 17(4), 617–637 (2007)CrossRefMathSciNetzbMATHGoogle Scholar
  5. 5.
    Neuböck, T., Neumayr, B., Schrefl, M., Schütz, C.: Ontology-driven business intelligence for comparative data analysis. In: Zimányi, E. (ed.) eBISS 2013. LNBIP, vol. 172, pp. 77–120. Springer, Heidelberg (2014) CrossRefGoogle Scholar
  6. 6.
    Nguyen, V., Bodenreider, O., Sheth, A.P.: Don’t like RDF reification?: making statements about statements using singleton property. In: Proceedings of the 23rd International World Wide Web Conference, WWW 2014, pp. 759–770 (2014)Google Scholar
  7. 7.
    Schütz, C., Neumayr, B., Schrefl, M.: Business model ontologies in OLAP cubes. In: Salinesi, C., Norrie, M.C., Pastor, Ó. (eds.) CAiSE 2013. LNCS, vol. 7908, pp. 514–529. Springer, Heidelberg (2013) CrossRefGoogle Scholar
  8. 8.
    Zhao, P., Li, X., Xin, D., Han, J.: Graph cube: on warehousing and OLAP multidimensional networks. In: Proceedings of the ACM SIGMOD International Conference on Management of Data, SIGMOD 2011, pp. 853–864 (2011)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Bernd Neumayr
    • 1
    Email author
  • Christoph G. Schuetz
    • 1
  • Michael Schrefl
    • 1
  1. 1.Johannes Kepler University LinzLinzAustria

Personalised recommendations