OLAP for Multidimensional Semantic Web Databases

Conference paper
Part of the Lecture Notes in Business Information Processing book series (LNBIP, volume 206)

Abstract

Semantic Web (SW) and web data have become increasingly important sources to support Business Intelligence (BI), but it is difficult to manage due to its scalability in their volumes, inconsistency in semantics and complexity in representations. On-Line Analytical Processing (OLAP) is an important tool in analysing large and complex BI data, but it lacks the capability of processing disperse SW data due to the nature of its design. A new concept with a richer vocabulary than the existing ones for OLAP is needed to model distributed multidimensional semantic web databases. In this paper we proposed a new OLAP framework with multiple layers including additional vocabulary, extended OLAP operators, and SPARSQL to model heterogeneous semantic web data, unify multidimensional structures, and provide new enabling functions for interoperability. We present the framework with examples to demonstrate its capability to unify RDF Data Cube (QB) [2] and QB4OLAP [1] with additional vocabulary elements to handle both informational and topological data [3] in Graph OLAP. It is also able to compose multiple databases (e.g. energy consumptions and property market values etc.) to generate observations through semantic pipe-like operators.

Keywords

On-Line Analytical Processing Business Intelligence Semantic web Data management RDF vocabulary 

References

  1. 1.
    Etcheverry, L., Vaisman, A.: QB4OLAP: a new vocabulary for OLAP cubes on the semantic web. In: Proceedings of COLD 2012: 3rd International Workshop on Consuming Linked Data, 11–12 November 2012Google Scholar
  2. 2.
    The RDF Data Cube Vocabulary. http://www.w3.org/TR/2012/WD-vocab-data-cube-20120405/. Accessed 5 April 2012
  3. 3.
    Chen, C., Yahn, X., Zhu, F., Han, J., Yu, P.S.: Graph OLAP: towards online analytical processing on graphs. In: Proceedings of the Eighth IEEE International Conference on Data Mining (2008)Google Scholar
  4. 4.
    Zhao, P., Li, X., Xin, D., Han, J.: Graph cube: on warehousing and OLAP multidimensional networks. In: Proceedings of the Sigmod Conference, Athens, Greece (2011)Google Scholar
  5. 5.
    Berlanga, R., Romero, O., Simitsis, A., Nebot, V., Pedersen, T.B., Abelló, A., Aramburu, M.J.: Semantic web technologies for business intelligence. In: Zorrilla, M.E., Mazón, J.-N., Ferrández, Ó., Garrigós, I., Daniel, F., Trujillo, J. (eds.) Business Intelligence Applications and the Web: Models, Systems and Technologies, pp. 310–339 (2012). doi:10.4018/978-1-61350-038-5.ch014
  6. 6.
    Kämpgen, B., O’Rain, S., Harth, A.: Interacting with statistical linked data via OLAP operations. In: Proceedings of the International Workshop on Interacting with Linked Data, pp. 36–49 (2012)Google Scholar
  7. 7.
    Beheshti, S.-M., Benatallah, B., Motahari-Nezhad, H.R., Allahbakhsh, M.: A framework and a language for on-line analytical processing on graphs. In: Wang, X., Cruz, I., Delis, A., Huang, G. (eds.) WISE 2012. LNCS, vol. 7651, pp. 213–227. Springer, Heidelberg (2012)CrossRefGoogle Scholar
  8. 8.
    Morbidoni, C., Polleres, A., Tummarello, G., Phuoc, D.L.: Semantic Web pipes. Technical report DERI-TR-2007-11-07, DERI Galway. December 2007Google Scholar
  9. 9.
    Chen, C., Yan, X., Zhu, F., Han, J., Yu, P.S.: Graph OLAP: a multi-dimensional framework for graph data analysis. Knowl. Inf. Syst. 21, 41–63 (2009). Springer, LondonCrossRefGoogle Scholar
  10. 10.
    Qu, Q., Zhu, F., Yan, X., Han, J., Yu, P.S., Li, Hongyan: Efficient topological OLAP on information networks. In: Yu, J.X., Kim, M.H., Unland, R. (eds.) DASFAA 2011, Part I. LNCS, vol. 6587, pp. 389–403. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  11. 11.
    Etcheverry, L., Vaisman, A.A.: Enhancing OLAP analysis with Web cubes. In: Simperl, E., Cimiano, P., Polleres, A., Corcho, O., Presutti, V. (eds.) ESWC 2012. LNCS, vol. 7295, pp. 469–483. Springer, Heidelberg (2012)CrossRefGoogle Scholar
  12. 12.
    Kämpgen, B., Harth, A.: Transforming statistical linked data for use in OLAP systems. In: Proceedings of the 7th International Conference on Semantic Systems, Graz, Austria, pp. 33–40, 07–09 September 2011Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  1. 1.Faculty of Engineering and ComputingCoventry UniversityCoventryUK

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