Semantic Cockpit: An Ontology-Driven, Interactive Business Intelligence Tool for Comparative Data Analysis

  • Bernd Neumayr
  • Michael Schrefl
  • Konrad Linner
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6999)


Business analysts frequently use Cockpits or Dashboards as front ends to data warehouses for inspecting and comparing multi-dimensional data at various levels of detail. These tools, however, perform badly in supporting a business analyst in his or her business intelligence task of understanding and evaluating a business within its environmental context through comparative data analysis. With important business knowledge either unrepresented or represented in a form not processable by automatic reasoning, the analyst is limited in the analyses that can be formulated and she or he heavily suffers from information overload with the need to re-judge similar situations again and again, and to re-discriminate between already explained and novel relationships between data. In an ongoing research project we try to overcome these limitations by applying and extending semantic technologies, such as ontologies and business rules, for comparative data analysis. The resulting Semantic Cockpit assists and guides the business analyst due to reasoning about various kinds of knowledge, explicitly represented by machine-processable ontologies, such as organisation-internal knowledge, organisation external domain knowledge, the semantics of measures and scores, knowledge about insights gained from previous analysis, and knowledge about how to act upon unusually low or high comparison scores. This paper outlines the architecture of the Semantic Cockpit and introduces its core ideas by a sample use case.


Data Warehouse Domain Ontology Business Intelligence Anti Depression Business Analyst 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Baader, F., Sattler, U.: Description logics with aggregates and concrete domains. Inf. Syst. 28(8), 979–1004 (2003)CrossRefzbMATHGoogle Scholar
  2. 2.
    Calvanese, D., Kharlamov, E., Nutt, W., Thorne, C.: Aggregate queries over ontologies. In: ONISW 2008: Proceeding of the 2nd International Workshop on Ontologies and Information Systems for the Semantic Web, pp. 97–104. ACM, New York (2008)Google Scholar
  3. 3.
    Golfarelli, M., Maio, D., Rizzi, S.: The dimensional fact model: A conceptual model for data warehouses. Int. J. Cooperative Inf. Syst. 7(2-3), 215–247 (1998)CrossRefGoogle Scholar
  4. 4.
    Khouri, S., Bellatreche, L.: A methodology and tool for conceptual designing a data warehouse from ontology-based sources. In: Song II, Y., Ordonez, C. (eds.) DOLAP, pp. 19–24. ACM, New York (2010)Google Scholar
  5. 5.
    Nebot, V., Llavori, R.B., Pérez-Martínez, J.M., Aramburu, M.J., Pedersen, T.B.: Multidimensional integrated ontologies: A framework for designing semantic data warehouses. J. Data Semantics 13, 1–36 (2009)CrossRefGoogle Scholar
  6. 6.
    Niemi, T., Niinimäki, M.: Ontologies and summarizability in olap. In: SAC, pp. 1349–1353 (2010)Google Scholar
  7. 7.
    Pardillo, J., Mazón, J.-N., Trujillo, J.: Extending ocl for olap querying on conceptual multidimensional models of data warehouses. Inf. Sci. 180(5), 584–601 (2010)CrossRefGoogle Scholar
  8. 8.
    Romero, O., Abelló, A.: A framework for multidimensional design of data warehouses from ontologies. Data Knowl. Eng. 69(11), 1138–1157 (2010)CrossRefGoogle Scholar
  9. 9.
    Sell, D., da Silva, D.C., Beppler, F.D., Napoli, M., Ghisi, F.B., dos Santos Pacheco, R.C., Todesco, J.L.: Sbi: a semantic framework to support business intelligence. In: Duke, A., Hepp, M., Bontcheva, K., Vilain, M.B. (eds.) OBI. ACM International Conference Proceeding Series, vol. 308, p. 11. ACM, New York (2008)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Bernd Neumayr
    • 1
  • Michael Schrefl
    • 1
  • Konrad Linner
    • 2
  1. 1.Department of Business Informatics - Data & Knowledge EngineeringJohannes Kepler University LinzLinzAustria
  2. 2.solvistas GmbHLinzAustria

Personalised recommendations