The Science of Conceptual Modelling

  • Bernhard Thalheim
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6860)

Abstract

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.

Keywords

Application Domain Design Science Abstraction Layer Business User Software Process Improvement 
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.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Bjørner, D.: Software Engineering 3: Domains, requirements, and software design. Springer, Berlin (2006)MATHGoogle Scholar
  2. 2.
    Heinrich, L.J., Heinzl, A., Riedl, R.: Wirtschaftsinformatik: Einführung und Grundlegung, 4th edn. Springer, Berlin (2011)CrossRefGoogle Scholar
  3. 3.
    Hevner, A., March, S., Park, J., Ram, S.: Design science in information systems research. MIS Quaterly 28(1), 75–105 (2004)Google Scholar
  4. 4.
    Humphrey, W.S.: Managing the Software Process. Addison-Wesley, Reading (1989)Google Scholar
  5. 5.
    ISO/IEC. Information technology - process assessment - part 2: Performing an assessment. IS 15504-2:2003 (2003)Google Scholar
  6. 6.
    Jaakkola, H., Thalheim, B.: Framework for high-quality software design and development: a systematic approach. IET Software 4(2), 105–118 (2010)CrossRefGoogle Scholar
  7. 7.
    Mahr, B.: Information science and the logic of models. Softw. Syst. Model. 8, 365–383 (2009)CrossRefGoogle Scholar
  8. 8.
    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
  9. 9.
    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
  10. 10.
    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
  11. 11.
    Safra, J.E., Yeshua, I., et al.: Encyclopædia Britannica. Merriam-Webster (2003)Google Scholar
  12. 12.
    Samuel, A., Weir, J.: Introduction to Engineering: Modelling, Synthesis and Problem Solving Strategies. Elsevier, Amsterdam (2000)Google Scholar
  13. 13.
    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
  14. 14.
    Schewe, K.-D., Thalheim, B.: Reasoning about web information systems using story algebra. In: Benczúr, A.A., Demetrovics, J., Gottlob, G. (eds.) ADBIS 2004. LNCS, vol. 3255, pp. 54–66. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  15. 15.
    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
  16. 16.
    Thalheim, B.: Entity-relationship modeling – Foundations of database technology. Springer, Berlin (2000)CrossRefMATHGoogle Scholar
  17. 17.
    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, Amsterdam (2010)Google Scholar
  18. 18.
    Thalheim, B.: Towards a theory of conceptual modelling. Journal of Universal Computer Science 16(20), 3102–3137 (2010), http://www.jucs.org/jucs_16_20/towards_a_theory_of MATHGoogle Scholar
  19. 19.
    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
  20. 20.
    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

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Bernhard Thalheim
    • 1
  1. 1.Computer Science InstituteChristian-Albrechts-University KielKielGermany

Personalised recommendations