Display Models - ways to classify visual representations

Article English OPEN
Roberts, Jonathan C. (2000)
  • Publisher: SETO, London, UK
  • Subject: QA76

Visualizations are generated of diverse data and use many different techniques and visual methods. It is often beneficial to evaluate what is being visualized and how the visualization is made-up. Such an analysis may aid the developer, to understand what `tools' are available, and help the user to reference and compare different realizations. Display models specifically classify the data by what type of output can be created. We review many `display oriented models' and discuss important aspects of these methods and ideas. In presenting these models we encourage their use. In particular we focus on the symbolic reference model of Jacques Bertin. He used this model to describe images and 2D visualizations. We translate Bertin's scheme into an algebraic form as a method to describe visualizations.
  • References (22)
    22 references, page 1 of 3

    [1] J. Bertin. Graphics and graphic information-processing. Walter de Gruyter, 1981. William J. Berg and Paul Scott (Translators).

    [2] J. Bertin. Semiology of Graphics, translation from SeĀ“milogie graphique (1967). The University of Winsonsin Press, 1983. William J. Berg (Translator).

    [3] C. G. Beshers and S. K. Feiner. Automated design of data visualizations. In L. Rosenblum, R. A. Earnshaw, J. Encarnacao, H. Hagen, A. Kaufman, S. Klimenko, G. Nielson, F. Post, and D. Thalmann, editors, Scientific Visualization Advances and Challenges, pages 87-102. IEEE Computer Society Press and Academic Press, 1994.

    [4] K. Brodlie. A classification scheme for scientific visualization. In R. E. Earnshaw and D. Watson, editors, Animation and Scientific Visualization - Tools and Applications, pages 125-140. Academic Press, 1993.

    [5] B. M. Collins. Data visualization - has it all been seen before? In R. E. Earnshaw and D. Watson, editors, Animation and Scientific Visualization - Tools and Applications, pages 3-28. Academic Press, 1992. 0-12-227745-7.

    [6] R. A. Earnshaw and N. Wiseman. An Introductory Guide to Scientific Visualization. Springer-Verlag, 1992.

    [7] B. Fortner. The Data Handbook (Second Edition) - A guide to Understanding the organisation and Visualization of Technical Data. Springer-Verlag, 1995.

    [8] R. B. Haber and D. A. McNabb. Visualization idioms: A conceptual model for scientific visualization systems. In B. Shriver, G. M. Nielson, and L. J. Rosenblum, editors, Visualization in Scientific Computing, pages 74-93. IEEE Computer Society Press, 1990.

    [9] M.-A. Halse, D. Young, and L. McCormick. IRIS Explorer User's Guide. Silicon Graphics Computer Systems - Silicon Graphics Inc., 1992. (Document Number 007-1371- 020).

    [10] W. L. Hibbard, C. R. Dyer, and B. E. Paul. A lattice model for data display. In Proceedings Visualization '94 - sponsored by the IEEE Computer Society, pages 310-317, 1994.

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