The Value of Information Visualization

  • Jean-Daniel Fekete
  • Jarke J. van Wijk
  • John T. Stasko
  • Chris North
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4950)


Researchers and users of Information Visualization are convinced that it has value. This value can easily be communicated to others in a face-to-face setting, such that this value is experienced in practice. To convince broader audiences, and also, to understand the intrinsic qualities of visualization is more difficult, however. In this paper we consider information visualization from different points of view, and gather arguments to explain the value of our field.


Perceptual Inference Exploratory Data Analysis Information Visualization Preattentive Processing Perceptual Chunk 
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.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Anscombe, F.: Graphs in statistical analysis. American Statistician 27(1), 17–21 (1973)CrossRefGoogle Scholar
  2. 2.
    Card, S.K., Mackinlay, J., Shneiderman, B. (eds.): Readings in Information Visualization – Using Vision to Think. Morgan Kaufmann, San Francisco (1998)Google Scholar
  3. 3.
    Chincor, N., Lewis, D., Hirschman, L.: Evaluating message understanding systems: An analysis of the third message understanding conference (MUC-3). Computational Linguistics 19(3), 409–449 (1993)Google Scholar
  4. 4.
    Gilbert, E.W.: Pioneer Maps of Health and Disease in England. Geographical Journal 124, 172–183 (1958)CrossRefGoogle Scholar
  5. 5.
    Johnson, B., Shneiderman, B.: Tree-maps: a space-filling approach to the visualization of hierarchical information structures. In: VIS ’91: Proceedings of the 2nd conference on Visualization ’91, Los Alamitos, CA, USA, pp. 284–291. IEEE Computer Society Press, Los Alamitos (1991)Google Scholar
  6. 6.
    Keim, D., Andrienko, G., Fekete, J.-D., Görg, C., Kohlhammer, J., Melançon, G.: Visual Analytics: Definition, Process, and Challenges. In: Kerren, A., Stasko, J.T., Fekete, J.-D., North, C.J. (eds.) Information Visualization. LNCS, vol. 4950, Springer, Heidelberg (2008)Google Scholar
  7. 7.
    Kerren, A., Stasko, J.T., Fekete, J.-D., North, C.J. (eds.): Information Visualization. LNCS, vol. 4950. Springer, Heidelberg (2008)Google Scholar
  8. 8.
    Koedinger, K.R., Anderson, J.R.: Abstract planning and perceptual chunks: Elements of expertise in geometry. Cognitive Science 14(4), 511–550 (1990)CrossRefGoogle Scholar
  9. 9.
    Koffa, K.: Principles of Gestalt Psychology. Routledge & Kegan Paul Ltd, London (1935)Google Scholar
  10. 10.
    Larkin, J.H., Simon, H.A.: Why a diagram is (sometimes) worth 10,000 words. Cognitive Science 11, 65–100 (1987)CrossRefGoogle Scholar
  11. 11.
    Lin, X.: Map displays for information retrieval. Journal of the American Society for Information Science 48(1), 40–54 (1997)CrossRefGoogle Scholar
  12. 12.
    Marey, E.: La Méthode Graphique. Paris (1885)Google Scholar
  13. 13.
    McLachlan, P., Munzner, T., Koutsofios, E., North, S.: Liverac: Interactive visual exploration of system management time-series data. In: SIGCHI Conference on Human Factors in Computing Systems (CHI 2008), ACM Press, New York (2008)Google Scholar
  14. 14.
    Noack, A.: Energy-based clustering of graphs with nonuniform degrees. In: Healy, P., Nikolov, N.S. (eds.) GD 2005. LNCS, vol. 3843, pp. 309–320. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  15. 15.
    Norman, D.A.: Things That Make Us Smart: Defending Human Attributes in the Age of the Machine. Addison-Wesley Longman Publishing Co., Inc., Boston (1993)Google Scholar
  16. 16.
    Perer, A., Shneiderman, B.: Integrating statistics and visualization: Case studies of gaining clarity during exploratory data analysis. In: SIGCHI Conference on Human Factors in Computing Systems (CHI 2008), ACM Press, New York (2008)Google Scholar
  17. 17.
    Plaisant, C.: The challenge of information visualization evaluation. In: AVI ’04: Proceedings of the working conference on Advanced visual interfaces, pp. 109–116. ACM Press, New York (2004)CrossRefGoogle Scholar
  18. 18.
    Popper, K.R.: The Logic of Scientific Discovery. Basic Books, New York (1959)zbMATHGoogle Scholar
  19. 19.
    Pousman, Z., Stasko, J., Mateas, M.: Casual information visualization: Depictions of data in everyday life. IEEE Transactions on Visualization and Computer Graphics 13(6), 1145–1152 (2007)CrossRefGoogle Scholar
  20. 20.
    Saraiya, P., North, C., Lam, V., Duca, K.: An insight-based longitudinal study of visual analytics. IEEE Transactions on Visualization and Computer Graphics 12(6), 1511–1522 (2006)CrossRefGoogle Scholar
  21. 21.
    Shannon, C.E., Weaver, W.: A Mathematical Theory of Communication. University of Illinois Press, Champaign (1963)Google Scholar
  22. 22.
    Spence, I., Garrison, R.F.: A remarkable scatterplot. The American Statistician, 12–19 (1993)Google Scholar
  23. 23.
    Triesman, A.: Preattentive processing in vision. Computer Vision, Graphics, and Image Processing 31(2), 156–177 (1985)CrossRefGoogle Scholar
  24. 24.
    Tufte, E.R.: The Visual Display of Quantitative Information. Graphics Press, Cheshire (1983)Google Scholar
  25. 25.
    Tufte, E.R.: Envisioning Information. Graphics Press, Cheshire (1990)Google Scholar
  26. 26.
    Tufte, E.R.: Visual Explanations: Images and Quantities, Evidence and Narrative. Graphics Press, Cheshire (1997)zbMATHGoogle Scholar
  27. 27.
    van Wijk, J.J.: The value of visualization. In: Proceedings IEEE Visualization 2005, pp. 79–86 (2005)Google Scholar
  28. 28.
    van Wijk, J.J., van de Wetering, H.: Cushion treemaps. In: Proceedings 1999 IEEE Symposium on Information Visualization (InfoVis’99), pp. 73–78. IEEE Computer Society Press, Los Alamitos (1999)CrossRefGoogle Scholar
  29. 29.
    Voorhees, E., Harman, D.: Overview of the sixth Text Retrieval Conference. Information Processing and Management 36(1), 3–35 (2000)CrossRefGoogle Scholar
  30. 30.
    Ware, C.: Information Visualization: Perception for Design. Morgan Kaufmann Publishers Inc., San Francisco (2004)Google Scholar
  31. 31.
    Wattenberg, M., Kriss, J.: Designing for social data analysis. IEEE Transactions on Visualization and Computer Graphics 12(4), 549–557 (2006)CrossRefGoogle Scholar
  32. 32.
    Williamson, C., Shneiderman, B.: The dynamic homefinder: evaluating dynamic queries in a real-estate information exploration system. In: SIGIR ’92: Proceedings of the 15th annual international ACM SIGIR conference on Research and development in information retrieval, pp. 338–346. ACM Press, New York (1992)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Jean-Daniel Fekete
    • 1
  • Jarke J. van Wijk
    • 2
  • John T. Stasko
    • 3
  • Chris North
    • 4
  1. 1.INRIAUniversité Paris-SudOrsay CedexFrance
  2. 2.Department of Mathematics and Computing ScienceEindhoven University of TechnologyMB EindhovenThe Netherlands
  3. 3.School of Interactive ComputingCollege of Computing & GVU Center, Georgia Institute of TechnologyAtlantaUSA
  4. 4.Dept of Computer ScienceVirginia TechBlacksburgUSA

Personalised recommendations