Skip to main content

Architectures for Evaluating the Quality of Information Models — A Meta and an Object Level Comparison

  • Conference paper
  • First Online:

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1728))

Abstract

The evaluation of information models is an outstanding research field in information systems engineering. From a theoretical oriented research viewpoint, it has to be questioned whether it is possible to evaluate artefacts with respect to philosophical and decision theory oriented aspects. Basing on the theoretical assumption that information modeling is a decision problem, this article deals with model evaluation approaches discussed in literature. Approaches will be compared not only on a meta level (ontological and epistemological assumptions) but also on an object level (evaluation of information models). The Frameworks of Moody/Shanks, Krogstie/Lindland/Sindre and the Guidelines of Modeling will be described and compared.

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Bitz, M.: Decision Theory. Munich 1981. (in german).

    Google Scholar 

  2. Burrell, G.; Morgan, G.: Sociological Paradigms and Organisational Analysis. London et al. 1979.

    Google Scholar 

  3. Darke, P.; Shanks, G.: Stakeholder Viewpoints in Requirements Definition. A Framework for Understanding Viewpoint Development Approaches. Requirements Engineering 2/1996, pp. 88–105.

    Google Scholar 

  4. Falkenberg, E.D. et al: FRISCO. A Framework of Information Systems. Summary of the FRISCO Report. December 1996 (http://leidenuniv.nl/publ./rul/fri-w60.zp, 4.4.1997).

  5. Fox, M.S.; Grüninger, M.: Ontologies for Enterprise Modelling. In: Enterprise Engineering and Integration. Building International Consensus. Proceedings of ICEIMT’ 97, International Conference on Enterprise Integration and Modeling Technology. Hrsg.: K. Kosanke, J.G. Nell. Berlin et al. 1997, S. 190–200.

    Google Scholar 

  6. Hirschheim, R.; Iivari, J.; Klein, H.K.: A Comparison of five alternative approaches to information systems development. AUSTRALIAN JOURNAL OF INFORMATION SYSTEMS 4/1998. (also http://www.cba.uh.edu/~parks/fis/sad5.htm, 16.3.1999).

  7. Inwood, M.J.: Weltanschauung. In: Honderich, T. (Ed.). The Oxford Companion to Philosophy. Oxford 1995, p. 909.

    Google Scholar 

  8. Krogstie, J.: Conceptual Modeling for Computerized Information Systems Support in Organizations. PhD Thesis, University of Trondheim. Trondheim 1995.

    Google Scholar 

  9. Krogstie, J.; Lindland, O.I.; Sindre, G.: Towards a Deeper Understanding of Quality in Requirements Engineering. In: Proceedings of the 7th Conference on Advanced Information Systems Engineering (CAiSE’ 95). Ed. by J. Iivari, K. Lyytinen, M. Rossi. Berlin 1995, pp. 82–95.

    Google Scholar 

  10. Krogstie, J.; Lindland, O.I.; Sindre, G.: Defining Quality Aspects for Conceptual Models. In: Proceedings of the International Conference on Information System Concepts (ISCO3). Towards a Consolidation of Views. Marburg 1995. Preprint.

    Google Scholar 

  11. Laux, H.: Decision theory. 4th Ed., Berlin et al. 1998.

    Google Scholar 

  12. Lindland, O. I.; Sindre, G.; Solvberg, A.: Understanding Quality in Conceptual Modeling. IEEE SOFTWARE 2/1994, pp. 42–49.

    Article  Google Scholar 

  13. Mingers, J.C.: Information and Meaning: foundations for an intersubjective account. INFORMATION SYSTEMS JOURNAL 1995, pp. 285–306.

    Google Scholar 

  14. Moody, D.L.: Metrics for Evaluating the Quality of Entity Relationship Models. In: Conceptual Modeling-ER’ 98. 17th International Conference on Conceptual Modeling. T.W. Ling, S. Ram, M.L Lee. Singapore, November 1998, pp. 211–225.

    Google Scholar 

  15. Moody, D.L.; Shanks, S.: What Makes a Good Data Model? Evaluating the Quality of Entity Relationship Models. In: Loucopoulos, P. (Ed.). Entity-Relationship-Approach — ER’ 94. Business Modelling and Re-Engineering. 13th International Conference on the Entity-Relationship Approach. Proceedings. Berlin et al.1994, pp. 94–111.

    Google Scholar 

  16. Moody, D.L.; Shanks, G.: What Makes a Good Data Model? A Framework for Evaluating and Improving the Quality of Entity Relationship Models. Australian Computer Journal 3/1998, pp. 97–110.

    Google Scholar 

  17. Moody, D.; Shanks, G.; Darke, P.: Improving the Quality of Entity Relationship Models-Experience in Research and Practice. In: Conceptual Modeling — ER’ 98. 17th International Conference on Conceptual Modeling. T.W. Ling, S. Ram, M.L. Lee. (Eds.). Singapore, November 1998, 255–276.

    Google Scholar 

  18. Rescher, N.: Objectivity. The Obligations of Impersonal Reason. Notre Dame, London 1997.

    Google Scholar 

  19. Schütte, R.: Guidelines of Reference Modeling. Construction configurative and adaptable models. Wiesbaden 1998. (in german).

    Google Scholar 

  20. Schütte, R.; Rotthowe, T.: The Guidelines of Modelling as an approach to enhance the quality of information models. In: Conceptual Modeling-ER’ 98. 17th International ERConference, Singapore, November 16–19, 1998. T. W. Ling, S. Ram, M. L. Lee (Eds.), Berlin et al. 1998, pp. 240–254.

    Google Scholar 

  21. Shanks, G.; Darke, P.: Understanding Data Quality in Data Warehousing: A Semiotic Approach. Proceedings of the Information Quality Conference, Massachusetts Institute of Technology. November 1998 (Preprint).

    Google Scholar 

  22. Shanks, G.; Darke, P.: Quality in Conceptual Modelling: Linking Theory and Practice. In: Proceedings of the Asia-Pacific Conference on Information Systems (PACIS). Brisbane 1997, pp. 805–814.

    Google Scholar 

  23. Stegmüller, W.: Experience, Fixing, Hypothesis and simplicity of concept and theory formation in the theory of science. Problems and Results of the theory of science and analytical philosophy, Vol. II: Theory and Experience, Study version Part A, Berlin et al. 1970. (in german).

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 1999 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Schuette, R. (1999). Architectures for Evaluating the Quality of Information Models — A Meta and an Object Level Comparison. In: Akoka, J., Bouzeghoub, M., Comyn-Wattiau, I., Métais, E. (eds) Conceptual Modeling — ER ’99. ER 1999. Lecture Notes in Computer Science, vol 1728. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-47866-3_33

Download citation

  • DOI: https://doi.org/10.1007/3-540-47866-3_33

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-66686-8

  • Online ISBN: 978-3-540-47866-9

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics