Skip to main content
SpringerLink
Log in
Book cover

European Business Intelligence Summer School

eBISS 2015: Business Intelligence pp 32–61Cite as

Publishing OLAP Cubes on the Semantic Web

  • Conference paper
  • First Online:

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 253))

Abstract

The availability of large repositories of semantically annotated data on the web is opening new opportunities for enhancing Decision-Support Systems. In addition, the advent of initiatives such as Open Data and Open Government, together with the Linked Open Data paradigm, are promoting publication and sharing of multidimensional data (MD) on the web. In this paper we address the problem of representing MD data using Semantic Web (SW) standards. We discuss how MD data can be represented and queried directly over the SW, without the need to download data sets into local data warehouses. We first comment on the RDF Data Cube Vocabulary (QB), the current W3C recommendation, and show that it is not enough to appropriately represent and query MD data on the web. In order to be able to support useful Online Analytical Process (OLAP) analysis, extension to QB, denoted QB4OLAP, has been proposed. We provide an in-depth comparison between these two proposals, and show that extending QB with QB4OLAP can be done without re-writing the observations, (the largest part of a QB data set). We provide extensive examples of the QB4OLAP representation, using a portion of the Eurostat data set and the well-known Northwind database. Finally, we present a high-level query language, called QL, that allows OLAP users not familiar with SW concepts or languages, to write and execute OLAP operators without any knowledge of RDF or SPARQL, the standard data model and query language, respectively, for the SW. QL queries are automatically translated into SPARQL (using the QB4OLAP metadata) and executed over an endpoint.

This is a preview of subscription content, log in via an institution.

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   34.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   44.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Notes

  1. 1.

    http://okfn.org/opendata/.

  2. 2.

    http://opengovdata.org/.

  3. 3.

    http://epp.eurostat.ec.europa.eu/cache/ITY_SDDS/EN/migr_asyapp_esms.htm.

  4. 4.

    http://eurostat.linked-statistics.org/.

  5. 5.

    http://www.w3.org/TR/owl2-overview/.

  6. 6.

    http://SDMX.org.

  7. 7.

    http://www.w3.org/TR/2009/REC-skos-reference-20090818/.

  8. 8.

    http://purl.org/qb4olap/cubes.

  9. 9.

    http://www.w3.org/TR/r2rml/.

  10. 10.

    https://www.fing.edu.uy/inco/grupos/csi/apps/qb4olap/.

References

  1. Heath, T., Bizer, C.: Linked Data: Evolving the Web into a Global Data Space. Synthesis Lectures on the Semantic Web. Morgan & Claypool Publishers, San Rafael (2011)

    Google Scholar 

  2. Klyne, G., Carroll, J.J., McBride, B.: Resource description framework (RDF): Concepts and abstract syntax (2004). http://www.w3.org/TR/rdf-concepts/

  3. Brickley, D., Guha, R., McBride, B.: RDF vocabulary description language 1.0: RDF schema (2004). http://www.w3.org/TR/rdf-schema/

  4. Abelló, A., Darmont, J., Etcheverry, L., Golfarelli, M., Mazón, J., Naumann, F., Pedersen, T.B., Rizzi, S., Trujillo, J., Vassiliadis, P., Vossen, G.: Fusion cubes: towards self-service business intelligence. Int. J. Data Warehous. Min. 9(2), 66–88 (2013)

    Article  Google Scholar 

  5. Cyganiak, R., Reynolds, D.: The RDF Data Cube Vocabulary (W3C Recommendation) (2014). http://www.w3.org/TR/vocab-data-cube/

  6. Etcheverry, L., Vaisman, A.: QB4OLAP: a vocabulary for OLAP cubes on the semantic web. In: Proceedings of the 3rd International Workshop on Consuming Linked Data, COLD 2012, Boston, USA. CEUR-WS.org (2012)

    Google Scholar 

  7. Vaisman, A., Zimányi, E.: Data Warehouse Systems: Design and Implementation. Springer, Heidelberg (2014)

    Book  Google Scholar 

  8. Varga, J., Etcheverry, L., Vaisman, A.A., Romero, O., Pedersen, T.B., Thomsen, C.: Enabling OLAP on statistical linked open data. In: Proceedings of the 32nd IEEE International Conference on Data Engineering, ICDE 2016, Helsinki, Finland (2016, to appear)

    Google Scholar 

  9. Varga, J., Romero, O., Vaisman, A.A., Etcheverry, L., Pedersen, T.B., Thomsen, C.: Dimensional enrichment of statistical linked open data (2016) (Submitted for publication)

    Google Scholar 

  10. Prud’hommeaux, E., Seaborne, A.: SPARQL 1.1 Query Language for RDF (2011). http://www.w3.org/TR/sparql11-query/

  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)

    Chapter  Google Scholar 

  12. Etcheverry, L., Vaisman, A., Zimányi, E.: Modeling and querying data warehouses on the semantic web using QB4OLAP. In: Bellatreche, L., Mohania, M.K. (eds.) DaWaK 2014. LNCS, vol. 8646, pp. 45–56. Springer, Heidelberg (2014)

    Google Scholar 

  13. Nebot, V., Llavori, R.B.: Building data warehouses with semantic web data. Decis. Support Syst. 52(4), 853–868 (2012)

    Article  Google Scholar 

  14. Kämpgen, B., Harth, A.: Transforming statistical linked data for use in OLAP systems. In: Proceedings of the 7th International Conference on Semantic Systems, I-Semantics 2011, Graz, Austria, pp. 33–40 (2011)

    Google Scholar 

  15. Löser, A., Hueske, F., Markl, V.: Situational business intelligence. In: Castellanos, M., Dayal, U., Sellis, T. (eds.) BIRTE 2008. LNBIP, vol. 27, pp. 1–11. Springer, Heidelberg (2009)

    Chapter  Google Scholar 

  16. Ibragimov, D., Hose, K., Pedersen, T.B., Zimányi, E.: Towards exploratory OLAP over linked open data – a case study. In: Castellanos, M., Dayal, U., Pedersen, T.B., Tatbul, N. (eds.) BIRTE 2013 and 2014. LNBIP, vol. 206, pp. 114–132. Springer, Heidelberg (2015)

    Google Scholar 

  17. Gómez, L.I., Gómez, S.A., Vaisman, A.A.: A generic data model and query language for spatiotemporal OLAP cube analysis. In: Proceedings of the 15th International Conference on Extending Database Technology, EDBT 2012, pp. 300–311. ACM (2012)

    Google Scholar 

  18. Hurtado, C.A., Mendelzon, A.O., Vaisman, A.A.: Maintaining data cubes under dimension updates. In: Proceedings of the 15th International Conference on Data Engineering. ICDE 1999, Sydney, Australia, pp. 346–355. IEEE Computer Society (1999)

    Google Scholar 

  19. Vassiliadis, P.: Modeling multidimensional databases, cubes and cube operations. In: Proceedings of the 10th International Conference on Scientific and Statistical Database Management. SSDBM 1998, Capri, Italy, pp. 53–62. IEEE Computer Society (1998)

    Google Scholar 

  20. Ciferri, C., Ciferri, R., Gómez, L., Schneider, M., Vaisman, A., Zimányi, E.: Cube algebra: a generic user-centric model and query language for OLAP cubes. Int. J. Data Warehous. Min. 9(2), 39–65 (2013)

    Article  Google Scholar 

  21. SDMX: SDMX standards: Information model (2011). http://sdmx.org/wp-content/uploads/2011/08/SDMX_2-1-1_SECTION_2_InformationModel_201108.pdf

  22. Beckett, D., Berners-Lee, T.: Turtle - Terse RDF Triple Language (2011). http://www.w3.org/TeamSubmission/turtle/

  23. Hausenblas, M., Ayers, D., Feigenbaum, L., Heath, T., Halb, W., Raimond, Y.: The Statistical Core Vocabulary (SCOVO) (2011). http://vocab.deri.ie/scovo

  24. Cyganiak, R., Field, S., Gregory, A., Halb, W., Tennison, J.: Semantic statistics : bringing together SDMX and SCOVO. In: Proceedings of the WWW2010 Workshop on Linked Data on the Web, pp. 2–6. CEUR-WS.org (2010)

    Google Scholar 

  25. SDMX: Content Oriented Guidelines (2009). https://sdmx.org/?p=163

  26. Bouza, M., Elliot, B., Etcheverry, L., Vaisman, A.A.: Publishing and querying government multidimensional data using QB4OLAP. In: Proceedings of the 9th Latin American Web Congress, LA-WEB 2014, Ouro Preto, Minas Gerais, Brazil, pp. 82–90 (2014)

    Google Scholar 

  27. Etcheverry, L., Gómez, S., Vaisman, A.A.: Modeling and querying data cubes on the semantic web (2015). CoRR abs/1512.06080

    Google Scholar 

  28. Etcheverry, L., Vaisman, A.A.: Querying semantic web data cubes efficiently (2016) (Submitted for publication)

    Google Scholar 

Download references

Acknowledgments

The author is partially funded by the project PICT 2014 - 0787 CC 0800082612, awarded by the Argentinian Scientific Agency.

Author information

Authors and Affiliations

  1. Instituto Tecnológico de Buenos Aires, Buenos Aires, Argentina

    Alejandro Vaisman

Authors
  1. Alejandro Vaisman
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Alejandro Vaisman .

Editor information

Editors and Affiliations

  1. Dept. of Computer and Decision Engg., Universite Libre de Bruxelles, Brussels, Belgium

    Esteban Zimányi

  2. Database Techn. & Inf. Management Group, Universitat Politecnica de Cataluny, Barcelona, Spain

    Alberto Abelló

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer International Publishing Switzerland

About this paper

Cite this paper

Vaisman, A. (2016). Publishing OLAP Cubes on the Semantic Web. In: Zimányi, E., Abelló, A. (eds) Business Intelligence. eBISS 2015. Lecture Notes in Business Information Processing, vol 253. Springer, Cham. https://doi.org/10.1007/978-3-319-39243-1_2

Download citation

Publish with us

Policies and ethics

Search

Navigation