Making Data Meaningful: The Business Intelligence Model and Its Formal Semantics in Description Logics

  • Jennifer Horkoff
  • Alex Borgida
  • John Mylopoulos
  • Daniele Barone
  • Lei Jiang
  • Eric Yu
  • Daniel Amyot
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7566)


Business Intelligence (BI) offers great opportunities for strategic analysis of current and future business operations; however, existing BI tools typically provide data-oriented responses to queries, difficult to understand in terms of business objectives and strategies. To make BI data meaningful, we need a conceptual modeling language whose primitive concepts represent business objectives, processes, opportunities and threats. We have previously introduced such a language, the Business Intelligence Model (BIM). In this paper we consolidate and rationalize earlier work on BIM, giving a precise syntax, reducing the number of fundamental concepts by using meta-attributes, and introducing the novel notion of “pursuit”. Significantly, we also provide a formal semantics of BIM using a subset of the OWL Description Logic (DL). Using this semantics as a translation, DL reasoners can be exploited to (1) propagate evidence and goal pursuit in support of “what if?” reasoning, (2) allow extensions to the BIM language, (3) detect inconsistencies in specific BIM models, and (4) automatically classify defined concepts relative to existing concepts, organizing the model.


Business Intelligence Business Model Goal Modeling Situation Analysis Model Reasoning Goal Reasoning Formal Semantics Description Logics 


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  1. 1.
    Object Management Group, Business Process Modeling Notation (BPMN) Version 2.0 (2009),
  2. 2.
    Kaplan, R.S., Norton, D.P.: Strategy Maps: Converting Intangible Assets into Tangible Outcomes, pp. 1–4. Harvard Business School Press (September 2004)Google Scholar
  3. 3.
    Kaplan, R.S., Norton, D.P.: Balanced Scorecard: Translating Strategy into Action. Harvard Business School Press (1996)Google Scholar
  4. 4.
    Dealtry, T.R.: Dynamic SWOT Analysis. Dynamic SWOT Associates (1994)Google Scholar
  5. 5.
    Yu, E.: Towards modelling and reasoning support for early-phase requirements engineering. In: Proceedings of 3rd IEEE International Symposium on Requirements Engineering (RE 1997), vol. 97, pp. 226–235 (1997)Google Scholar
  6. 6.
    Dardenne, A., Lamsweerde, A.V., Fickas, S.: Goal-directed requirements acquisition. Science of Computer Programming 20(1-2), 3–50 (1993)zbMATHCrossRefGoogle Scholar
  7. 7.
    W3C, OWL 2 Web Ontology Language Manchester Syntax (2009),
  8. 8.
    Jiang, L., Barone, D., Amyot, D., Mylopoulos, J.: Strategic Models for Business Intelligence. In: Jeusfeld, M., Delcambre, L., Ling, T.-W. (eds.) ER 2011. LNCS, vol. 6998, pp. 429–439. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  9. 9.
    Barone, D., Jiang, L., Amyot, D., Mylopoulos, J.: Composite Indicators for Business Intelligence. In: Jeusfeld, M., Delcambre, L., Ling, T.-W. (eds.) ER 2011. LNCS, vol. 6998, pp. 448–458. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  10. 10.
    Barone, D., Yu, E., Won, J., Jiang, L., Mylopoulos, J.: Enterprise Modeling for Business Intelligence. In: van Bommel, P., Hoppenbrouwers, S., Overbeek, S., Proper, E., Barjis, J. (eds.) PoEM 2010. LNBIP, vol. 68, pp. 31–45. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  11. 11.
    Barone, D., Jiang, L., Amyot, D., Mylopoulos, J.: Reasoning with Key Performance Indicators. In: Johannesson, P., Krogstie, J., Opdahl, A.L. (eds.) PoEM 2011. LNBIP, vol. 92, pp. 82–96. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  12. 12.
    Borgida, A., Horkoff, J., Mylopoulos, J., Rosati, R.: Experiences in Mapping the Business Intelligence Model to Description Logics, and the Case for Parametric Concepts. In: Proceedings of the 2012 International Workshop on Description Logics, DL 2012 (2012)Google Scholar
  13. 13.
    Datamonitor, Global Credit & Charge Cards Industry Profile (2004)Google Scholar
  14. 14.
    Giorgini, P., Mylopoulos, J., Nicchiarelli, E., Sebastiani, R.: Formal Reasoning Techniques for Goal Models. In: Spaccapietra, S., March, S., Aberer, K. (eds.) Journal on Data Semantics I. LNCS, vol. 2800, pp. 1–20. Springer, Heidelberg (2003)CrossRefGoogle Scholar
  15. 15.
    Sebastiani, R., Giorgini, P., Mylopoulos, J.: Simple and Minimum-Cost Satisfiability for Goal Models. In: Persson, A., Stirna, J. (eds.) CAiSE 2004. LNCS, vol. 3084, pp. 20–35. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  16. 16.
    Amyot, D., Ghanavati, S., Horkoff, J., Mussbacher, G., Peyton, L., Yu, E.: Evaluating goal models within the goal-oriented requirement language. International Journal of Intelligent Systems 25(8), 841–877 (2010)CrossRefGoogle Scholar
  17. 17.
    Berardi, D., Calvanese, D., Degiacomo, G.: Reasoning on UML class diagrams. Artificial Intelligence 168(1-2), 70–118 (2005)MathSciNetzbMATHCrossRefGoogle Scholar
  18. 18.
    Wetzel, T.: States of Affairs. The Stanford Encyclopedia of Philosophy, Fall 2008 Edition (2008),
  19. 19.
    Masolo, C., Borgo, S., Gangemi, A., Guarino, N., Oltramari, A.: WonderWeb Deliverable D18. The WonderWeb Library of Foundational Ontologies and the DOLCE ontology (December 2003)Google Scholar
  20. 20.
    Krötzsch, M., Rudolph, S., Hitzler, P.: Description Logic Rules. In: Proceedings of the 18th European Conference on Artificial Intelligence (ECAI 2008), pp. 80–84 (2008)Google Scholar
  21. 21.
    Opdahl, A.L., Berio, G., Harzallah, M., Matulevicius, R.: An ontology for enterprise and information systems modelling. Applied Ontology 7(1), 49–92 (2012)Google Scholar
  22. 22.
    Du, J., Pan, J.Z.: Towards Practical ABox Abduction in Large OWL DL Ontologies. In: Artificial Intelligence, pp. 1160–1165 (2009)Google Scholar
  23. 23.
    Guarino, N., Welty, C.A.: An Overview of OntoClean. Handbook on Ontologies 48(1), 1–20 (2004)Google Scholar
  24. 24.
    Barone, D., Topaloglou, T., Mylopoulos, J.: Business Intelligence Modeling in Action: A Hospital Case Study. In: Ralyté, J., Franch, X., Brinkkemper, S., Wrycza, S. (eds.) CAiSE 2012. LNCS, vol. 7328, pp. 502–517. Springer, Heidelberg (2012)CrossRefGoogle Scholar
  25. 25.
    Bunge, M.: Treatise on Basic Philosophy: Vol 1-8. Ontology I The Furniture of the World Boston Reidel (1977)Google Scholar
  26. 26.
    Opdahl, A.L.: Anatomy of the Unified Enterprise Modelling Ontology. In: van Sinderen, M., Johnson, P. (eds.) IWEI 2011. LNBIP, vol. 76, pp. 163–176. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  27. 27.
    Borgida, A.: Description Logics in Data Management. Data Engineering 7(5), 671–682 (1995)CrossRefGoogle Scholar
  28. 28.
    Iannone, L., Rector, A.: Calculations in OWL. In: Proceedings of the 5th Workshop OWL: Experiences and Directions, OWLED (2008)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Jennifer Horkoff
    • 1
  • Alex Borgida
    • 2
  • John Mylopoulos
    • 1
  • Daniele Barone
    • 1
  • Lei Jiang
    • 1
  • Eric Yu
    • 3
  • Daniel Amyot
    • 4
  1. 1.Dept. of Computer ScienceUniversity of TorontoCanada
  2. 2.Dept. of Computer ScienceRutgers UniversityUSA
  3. 3.Faculty of InformationUniversity of TorontoCanada
  4. 4.EECSUniversity of OttawaCanada

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