The Science and Art of Conceptual Modelling

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7600)


Conceptual modelling is one of the central activities in Computer Science. Conceptual models are mainly used as intermediate artifact for system construction. They are schematic descriptions of a system, a theory, or a phenomenon of an origin thus forming a model. A conceptual model is a model enhanced by concepts. The process of conceptual modelling is ruled by the purpose of modelling and the models. It is based on a number of modelling acts, on a number of correctness conditions, on modelling principles and postulates, and on paradigms of the background or substance theories. Purposes determine the (surplus) value of a model. Conceptual modelling is performed by a modeller that directs the process based on his/her experience, education, understanding, intention and attitude. Conceptual models are products that are used by other stakeholders such as programmers, learners, business users, and evaluators. Conceptual models use a language as a carrier for the modelling artifact and are restricted by the expressiveness of this carrier.

This paper aims at a discussion of a general theory of modelling as a culture and an art. A general theory of modelling also considers modelling as an apprenticeship and as a technology. It is thus an art. Modelling is on of the main elements of Computer Science culture that consists of commonly accepted behaviour patterns, arts, consensus, institutions, and all other supporting means and thoughts.


conceptual modelling modelling workflow foundations of modelling 


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  1. 1.
    Bjørner, D.: Software Engineering 3: Domains, requirements, and software design. Springer, Berlin (2006)Google Scholar
  2. 2.
    Bjørner, D.: Domain engineering. COE Research Monographs, vol. 4. Japan Advanced Institute of Science and Technolgy Press, Ishikawa (2009)Google Scholar
  3. 3.
    Denning, P.J.: Great principles of computing (2007),
  4. 4.
    Gregor, S., Jones, D.: The anatomy of a design theory. Journal of Association for Information Systems 8(5), 312–335 (2007)Google Scholar
  5. 5.
    Halloun, I.A.: Modeling Theory in Science Education. Springer, Berlin (2006)Google Scholar
  6. 6.
    Heinrich, L.J., Heinzl, A., Riedl, R.: Wirtschaftsinformatik: Einführung und Grundlegung, 4th edn. Springer, Berlin (2011)Google Scholar
  7. 7.
    Hevner, A., March, S., Park, J., Ram, S.: Design science in information systems research. MIS Quaterly 28(1), 75–105 (2004)Google Scholar
  8. 8.
    Humphrey, W.S.: Managing the Software Process. Addison-Wesley (1989)Google Scholar
  9. 9.
    ISO/IEC. Information technology - process assessment - part 2: Performing an assessment IS (2003) 15504-2:2003Google Scholar
  10. 10.
    Jaakkola, H., Thalheim, B.: Framework for high-quality software design and development: a systematic approach. IET Software 4(2), 105–118 (2010)CrossRefGoogle Scholar
  11. 11.
    Kaschek, R.: Konzeptionelle Modellierung. PhD thesis. University Klagenfurt, Habilitationsschrift (2003)Google Scholar
  12. 12.
    Kidawara, Y., Zettsu, K., Kiyoki, Y., Jannaschk, K., Thalheim, B., Linna, P., Jaakkola, H., Duzí, M.: Knowledge modeling, management and utilization towards next generation web. In: Information Modelling and Knowledge Bases XXI, vol. 206, pp. 387–402. IOS Press (2010)Google Scholar
  13. 13.
    Klaus, G., Buhr, M. (eds.): Philosophisches Wörterbuch. VEB Bibliographisches Institut., Leipzig (1971)Google Scholar
  14. 14.
    Krauch, H.: System analysis. In: Seiffert, H., Radnitzky, G. (eds.) Handlexikon zur Wissenschaftstheorie, pp. 338–344. Deutscher Taschenbuch Verlag GmbH & Co. KG, München (1992)Google Scholar
  15. 15.
    Mahr, B.: Information science and the logic of models. Softw. Syst. Model 8, 365–383 (2009)CrossRefGoogle Scholar
  16. 16.
    March, S.T., Storey, V.C.: Design science in the information systems discipline: An introduction to the special issue on design science research. MIS Quarterly 4, 725–730 (2008)Google Scholar
  17. 17.
    Mesarovic, M.D., Takahara, Y.: General systems theory: Mathematical foundations. Academic Press, New York (1975)zbMATHGoogle Scholar
  18. 18.
    Mittelstraß, J. (ed.): Enzyklopädie Philosophie und Wissenschaftstheorie, J.B. Metzler, Stuttgart (2004)Google Scholar
  19. 19.
    Orellana, P.: Maieutic frame presense and quantity and quality of argumentation in a Paideia seminar. Doctor of philosophy, University of North Carolina at Chapel Hill (2008)Google Scholar
  20. 20.
    Ortner, E., Schienmann, B.: Normative Language Approach - a Framework for Understanding. In: Thalheim, B. (ed.) ER 1996. LNCS, vol. 1157, pp. 261–276. Springer, Heidelberg (1996)CrossRefGoogle Scholar
  21. 21.
    Paulk, M.C., Curtis, B., Chrissis, M.B., Weber, C.V.: Capability maturity model for software, version 1.1. Technical Report CMU/SEI-93-TR-024, Software Engineering Institute (February 1993)Google Scholar
  22. 22.
    Polya, G.: How to solve it: A new aspect of mathematical method. Princeton University Press, Princeton (1945)zbMATHGoogle Scholar
  23. 23.
    Safra, J.E., Yeshua, I., et al.: Encyclopædia Britannica. Merriam-Webster (2003)Google Scholar
  24. 24.
    Samuel, A., Weir, J.: Introduction to Engineering: Modelling, Synthesis and Problem Solving Strategies. Elsevier, Amsterdam (2000)Google Scholar
  25. 25.
    Saukkonen, S., Oivo, M.: Six step software process improvement method (in finnish; teollinen ohjelmistoprosessi. ohjelmistoprosessin parantaminen SIPI-menetelmällä). Tekes 64/98, Teknologiakatsaus (October 1998)Google Scholar
  26. 26.
    Schewe, K.-D., Thalheim, B.: Reasoning About Web Information Systems Using Story Algebras. In: Benczúr, A.A., Demetrovics, J., Gottlob, G. (eds.) ADBIS 2004. LNCS, vol. 3255, pp. 54–66. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  27. 27.
    Schewe, K.-D., Thalheim, B.: Usage-based storyboarding for web information systems. Technical Report 2006-13, Christian Albrechts University Kiel. Institute of Computer Science and Applied Mathematics, Kiel (2006)Google Scholar
  28. 28.
    Schewe, K.-D., Thalheim, B.: Semantics in Data and Knowledge Bases. In: Schewe, K.-D., Thalheim, B. (eds.) SDKB 2008. LNCS, vol. 4925, pp. 1–25. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  29. 29.
    Simsion, G.: Data modeling - Theory and practice. Technics Publications, LLC (2007)Google Scholar
  30. 30.
    Sriraman, B., English, L.: Theories about mathematics education. Springer, Berlin (2010)CrossRefGoogle Scholar
  31. 31.
    Stachowiak, H.: Modell. In: Seiffert, H., Radnitzky, G. (eds.) Handlexikon zur Wissenschaftstheorie, pp. 219–222. Deutscher Taschenbuch Verlag GmbH & Co. KG, München (1992)Google Scholar
  32. 32.
    Steinmüller, W.: Informationstechnologie und Gesellschaft: Einführung in die Angewandte Informatik. Wissenschaftliche Buchgesellschaft, Darmstadt (1993)Google Scholar
  33. 33.
    Thalheim, B.: Entity-relationship modeling – Foundations of database technology. Springer, Berlin (2000)zbMATHGoogle Scholar
  34. 34.
    Thalheim, B.: The conceptual framework to user-oriented content management. Series Frontiers in Arificial Intelligence. 154. Information Modelling and Knowledge Bases, XVII, 30–49 (2007)Google Scholar
  35. 35.
    Thalheim, B.: Model suites for multi-layered database modelling. In: Information Modelling and Knowledge Bases XXI. Frontiers in Artificial Intelligence and Applications, vol. 206, pp. 116–134. IOS Press (2010)Google Scholar
  36. 36.
    Thalheim, B.: Towards a theory of conceptual modelling. Journal of Universal Computer Science 16(20), 3102–3137 (2010), zbMATHGoogle Scholar
  37. 37.
    Thalheim, B.: The theory of conceptual models, the theory of conceptual modelling and foundations of conceptual modelling. In: The Handbook of Conceptual Modeling: Its Usage and Its Challenges, ch.17, pp. 547–580. Springer, Berlin (2011)Google Scholar
  38. 38.
    Venable, J.R.: Design Science Research Post Hevner et al.: Criteria, Standards, Guidelines, and Expectations. In: Winter, R., Zhao, J.L., Aier, S. (eds.) DESRIST 2010. LNCS, vol. 6105, pp. 109–123. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  39. 39.
    Wittgenstein, L.: Philosophical Investigations. Basil Blackwell, Malden (1958)Google Scholar

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© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  1. 1.Computer Science InstituteChristian-Albrechts-University KielKielGermany

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