Ontology-Based Big Dimension Modeling in Data Warehouse Schema Design

  • Xiufeng Liu
  • Nadeem Iftikhar
Conference paper
Part of the Lecture Notes in Business Information Processing book series (LNBIP, volume 157)


During data warehouse schema design, designers often encounter how to model big dimensions that typically contain a large number of attributes and records. To investigate effective approaches for modeling big dimensions is necessary in order to achieve better query performance, with respect to response time. In most cases, the big dimension modeling process is complicated since it usually requires accurate description of business semantics, multiple design revisions and comprehensive testings. In this paper, we present the design methods for modeling big dimensions, which include horizontal partitioning, vertical partitioning and their hybrid. We formalize the design methods, and propose an algorithm that describes the modeling process from an OWL ontology to a data warehouse schema. In addition, this paper also presents an effective ontology-based tool to automate the modeling process. The tool can automatically generate the data warehouse schema from the ontology of describing the terms and business semantics for the big dimension. In case of any change in the requirements, we only need to modify the ontology, and re-generate the schema using the tool. This paper also evaluates the proposed methods based on sample sales data mart.


OWL ontology Big dimension design DW schema Partitioning based design methods 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Abello, A., Romero, O.: Using Ontologies to Discover Facts IDs. In: DOLAP, pp. 3–10 (2010)Google Scholar
  2. 2.
    Abadi, D.J., Madden, S.R., Hachem, N.: Column-Store vs. Row-Stores: How Different Are They Really? In: SIGMOD, pp. 1–14 (2008)Google Scholar
  3. 3.
    Agrawal, S., Narasayya, V.R., Yang, B.: Integrating Vertical and Horizontal Partitioning into Automated Physical Database Design. In: SIGMOD, pp. 359–370 (2004)Google Scholar
  4. 4.
    Astrova, I., Korda, N., Kalja, A.: Storing OWL Ontologies in SQL Relational Databases. ECSE 1(4), 167–172 (2007)Google Scholar
  5. 5.
    Eberhart, A.: Automatic Generation of Java/SQL based Inference Engines from RDF Schema and RuleML. In: Horrocks, I., Hendler, J. (eds.) ISWC 2002. LNCS, vol. 2342, pp. 102–116. Springer, Heidelberg (2002)CrossRefGoogle Scholar
  6. 6.
    Gali, A., Chen, C.X., Claypool, K.T., Uceda-Sosa, R.: From Ontology to Relational Databases. In: ER Workshops, pp. 278–289 (2004)Google Scholar
  7. 7.
    Costa, M., Madeira, H.: Handling Big Dimensions in Distributed Data Warehouses using the DWS Technique. In: DOLAP, pp. 31–37 (2004)Google Scholar
  8. 8.
    Imhoff, C., Galemmo, N., Geiger, J.G.: Mastering Data Warehouse Design: Relational and Dimensional Techniques, pp. 285–317. John Wiley and Sons, NY (2003)Google Scholar
  9. 9.
    Kalyanpur, A., Pastor, D.J., Battle, S., Padget, J.: Automatic Mapping of OWL Ontologies into Java. In: SEKE, pp. 98–103 (2004)Google Scholar
  10. 10.
    Liu, X., Thomsen, C., Pedersen, T.B.: 3XL: Supporting Efficient Operations on Very Large OWL Lite Triple-stores. Information Systems 36(4), 765–781 (2011)CrossRefGoogle Scholar
  11. 11.
    Moody, D.L., Kortink, M.A.R.: From Er Models to Dimensional Models II: Advanced Design Issues. Business Intelligence Journal 8(4) (2003)Google Scholar
  12. 12.
    Navathe, S.: A Mixed Fragmentation Methodology For Initial Distributed Database Design. Journal of Computer and Software Engineering 3(4), 395–426 (1995)Google Scholar
  13. 13.
    Owl Description, (September 20, 2012)
  14. 14.
    Romero, O., Abello, A.: Automating Multidimensional Design from Ontologies. In: DOLAP, pp. 1–8 (2007)Google Scholar
  15. 15.
    Silverston, L., Inmon, W.H., Graziano, K.: The Data Model Resource Book: A Library of Logical Data Models and Data Warehouse Designs. John Wiley and Sons, NY (1997)Google Scholar
  16. 16.
    TPC-H, (September 20, 2012)
  17. 17.
    Vysniauskas, E., Nemuraite, L.: Transforming Ontology Representation from OWL to Relational Database. Information Technology and Control 35(3A), 333–343 (2006)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Xiufeng Liu
    • 1
  • Nadeem Iftikhar
    • 2
  1. 1.Department of Computer ScienceAalborg UniversityDenmark
  2. 2.Technology & BusinessUniversity College of Northern DenmarkDenmark

Personalised recommendations