Form-Semantics-Function – A Framework for Designing Visual Data Representations for Visual Data Mining

  • Simeon J. Simoff
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4404)


Visual data mining, as an art and science of teasing meaningful insights out of large quantities of data that are incomprehensible in another way, requires consistent visual data representations (information visualisation models). The frequently used expression "the art of information visualisation" appropriately describes the situation. Though substantial work has been done in the area of information visualisation, it is still a challenging activity to find out the methods, techniques and corresponding tools that support visual data mining of a particular type of information. The comparison of visualisation techniques across different designs is not a trivial problem either. This chapter presents an attempt for a consistent approach to formal development, evaluation and comparison of visualisation methods. The application of the approach is illustrated with examples of visualisation models for data from the area of team collaboration in virtual environments and from the results of text analysis.


Virtual World Target Space Visual Data Source Domain Visualisation Model 
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.


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  1. 1.
    Hetzler, B., Harris, W.M., Havre, S., Whitney, P.: Visualising the full spectrum of document relationships, in Structures and Relations in Knowledge Organisation. In: Proceedings of the Fifth International Society for Knowledge Organization (ISKO) Conference, Lille, France (1998)Google Scholar
  2. 2.
    Hetzler, B., Whitney, P., Martucci, L., Thomas, J.: Multi-faceted insight through interoperable visual information analysis paradigms. In: Proceedings of the 1998 IEEE Symposium on Information Visualization. IEEE Computer Society, Washington, DC (1998)Google Scholar
  3. 3.
    Brown, I.M.: A 3D user interface for visualisation of Web-based data-sets. In: Proceedings of the 6th ACM International Symposium on Advances in Geographic Information Systems. ACM, Washington, D.C (1998)Google Scholar
  4. 4.
    Noirhomme-Fraiture, M.: Multimedia support for complex multidimensional data mining. In: Proceedings of the First International Workshop on Multimedia Data Mining (MDM/KDD 2000), in conjunction with Sixth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining KDD 2000. ACM Press, Boston (2000)Google Scholar
  5. 5.
    Chen, C.: Information Visualization: Beyond the Horizon. Springer, London (2004)Google Scholar
  6. 6.
    Gross, M.: Visual Computing: The Integration of Computer Graphics. Springer, Heidelberg (1994)zbMATHGoogle Scholar
  7. 7.
    Nielson, G.M., Hagen, H., Muller, H.: Scientific Visualization: Overviews, Methodologies, and Techniques. IEEE Computer Society, Los Alamitos (1997)Google Scholar
  8. 8.
    Chen, C., Yu, Y.: Empirical studies of information visualization: A meta-analysis. International Journal of Human-Computer Studies 53(5), 851–866 (2000)zbMATHCrossRefGoogle Scholar
  9. 9.
    Hofmann, H., Siebes, A.P.J.M., Wilhelm, A.F.X.: Visualizing association rules with interactive mosaic plots. In: Proceedings of the Sixth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining KDD 2000. ACM, Boston (2000)Google Scholar
  10. 10.
    Crapo, A.W., Waisel, L.B., Wallace, W.A., Willemain, T.R.: Visualization and the process of modeling: A cognitive-theoretic approach. In: Proceedings of the Sixth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining KDD 2000. ACM, New York (2000)Google Scholar
  11. 11.
    Snowdon, D.N., Greenhalgh, C.M., Benford, S.D.: What You See is Not What I See: Subjectivity in virtual environments. In: Proceedings Framework for Immersive Virtual Environments (FIVE 1995). QMW University of London, UK (1995)Google Scholar
  12. 12.
    Damer, B.: Avatars. Peachpit Press, an imprint of Addison Wesley Longman (1998)Google Scholar
  13. 13.
    Maher, M.L., Simoff, S.J., Cicognani, A.: Understanding virtual design studios. Springer, London (2000)Google Scholar
  14. 14.
    Del Bimbo, A.: Visual Information Retrieval. Morgan Kaufmann Publishers, San Francisco (1999)Google Scholar
  15. 15.
    Gong, Y.: Intelligent Image Databases: Towards Advanced Image Retrieval. Kluwer Academic Publishers, Boston (1998)Google Scholar
  16. 16.
    Börner, K., Chen, C., Boyack, K.: Visualizing knowledge domains. Annual Review of Information Science &Technology, 179–355 (2003)Google Scholar
  17. 17.
    Kumaran, D., Maguire, E.A.: The human hippocampus: Cognitive maps or relational memory? The Journal of Neuroscience 25(31), 7254–7259 (2005)CrossRefGoogle Scholar
  18. 18.
    Choras, D.N., Steinmann, H.: Virtual reality: Practical applications in business and industry. Prentice-Hall, Upper Saddle River (1995)Google Scholar
  19. 19.
    Gore, R.: When the space shuttle finally flies. National Geographic 159, 317–347 (1981)Google Scholar
  20. 20.
    Lakoff, G., Johnson, M.: Metaphors We Live By. University of Chicago Press, Chicago (1980)Google Scholar
  21. 21.
    Lakoff, G.: The contemorary theory of metaphor, in Metaphor and Thought. In: Ortony, A. (ed.), pp. 202–251. Cambridge University Press, Cambridge (1993)Google Scholar
  22. 22.
    L’Abbate, M., Hemmje, M.: VIRGILIO - The metaphor definition tool, in Technical Report: rep-ipsi-1998-15. 2001, European Research Consortium for Informatics and Mathematics at FHG (2001)Google Scholar
  23. 23.
    Turner, M.: Design for a theory of meaning. In: Overton, W., Palermo, D. (eds.) The Nature and Ontogenesis of Meaning, pp. 91–107. Lawrence Erlbaum Associates, Mahwah (1994)Google Scholar
  24. 24.
    Turner, M., Fauconnier, G.: Conceptual integration and formal expression. Journal of Metaphor and Symbolic Activity 10(3), 183–204 (1995)CrossRefGoogle Scholar
  25. 25.
    Anderson, B., Smyth, M., Knott, R.P., Bergan, M., Bergan, J., Alty, J.L.: Minimising conceptual baggage: Making choices about metaphor. In: Cocton, G., Draper, S., Weir, G. (eds.) People and Computers IX, G, pp. 179–194. Cambridge University Press, Cambridge (1994)Google Scholar
  26. 26.
    Maher, M.L., Simoff, S.J., Cicognani, A.: Potentials and limitations of virtual design studios. Interactive Construction On-Line 1 (1997)Google Scholar
  27. 27.
    Berthold, M.R., Sudweeks, F., Newton, S., Coyne, R.: Clustering on the Net: Applying an autoassociative neural network to computer-mediated discussions. Journal of Computer Mediated Communication 2(4) (1997)Google Scholar
  28. 28.
    Berthold, M.R., Sudweeks, F., Newton, S., Coyne, R.: It makes sense: Using an autoassociative neural network to explore typicality in computer mediated discussions. In: Sudweeks, F., McLaughlin, M., Rafaeli, S. (eds.) Network and Netplay: Virtual Groups on the Internet, pp. 191–220. AAAI/MIT Press, Menlo Park, CA (1998)Google Scholar
  29. 29.
    Sudweeks, F., Simoff, S.J.: Complementary explorative data analysis: The reconciliation of quantitative and qualitative principles. In: Jones, S. (ed.) Doing Internet Research, pp. 29–55. Sage Publications, Thousand Oaks (1999)Google Scholar
  30. 30.
    Simoff, S.J., Maher, M.L.: Knowledge discovery in hypermedia case libraries - A methodological framework. In: Proceedings of the Fourth Australian Knowledge Acquisition Workshop AKAW 1999, in conjunction with 12th Australian Joint Conference on Artificial Intelligence, AI 1999, Sydney, Australia (1999)Google Scholar
  31. 31.
    Chen, C.: An information-theoretic view of visual analytics. IEEE Computer Graphics and Applications 28(1), 18–23 (2008)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Simeon J. Simoff
    • 1
  1. 1.School of Computing and Mathematics College of Heath and ScienceUniversity of Western SydneyAustralia

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