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Duke, D.J.; Brodlie, K.W.; Duce, D.A.; Herman, I. (2005)
Languages: English
Types: Article
Visualizers, like logicians, have long been concerned with meaning. Generalizing from MacEachren's overview of cartography, visualizers have to think about how people extract meaning from pictures (psychophysics), what people understand from a picture (cognition), how pictures are imbued with meaning (semiotics), and how in some cases that meaning arises within a social and/or cultural context. If we think of the communication acts carried out in the visualization process further levels of meaning are suggested. Visualization begins when someone has data that they wish to explore and interpret; the data are encoded as input to a visualization system, which may in its turn interact with other systems to produce a representation. This is communicated back to the user(s), who have to assess this against their goals and knowledge, possibly leading to further cycles of activity. Each phase of this process involves communication between two parties. For this to succeed, those parties must share a common language with an agreed meaning. We offer the following three steps, in increasing order of formality: terminology (jargon), taxonomy (vocabulary), and ontology. Our argument in this article is that it's time to begin synthesizing the fragments and views into a level 3 model, an ontology of visualization. We also address why this should happen, what is already in place, how such an ontology might be constructed, and why now.
  • The results below are discovered through our pilot algorithms. Let us know how we are doing!

    • 1. A.M. MacEachren, How Maps Work, The Guildford Press, 1995.
    • 2. M. Tory and T. Möller, “Rethinking Visualization: A High Level Taxonomy,” Proc. IEEE Symp. Information Visualization, IEEE CS Press, 2004, pp. 151-158.
    • 3. I. Herman, G. Melançon, and M.S. Marshall, “Graph Visualization and Navigation in Information Visualization: A Survey,” IEEE Trans. Visualization and Computer Graphics, vol. 6, no. 1, 2000, pp. 24-43.
    • 4. K.W. Brodlie, “A Classification Scheme for Scientific Visualization,” Animation and Scientific Visualization, R.A. Earnshaw and D. Watson, eds., Academic Press, 1993, pp. 120-140.
    • 5. P.R. Keller and M.M. Keller, Visual Cues: Practical Data Visualization, IEEE CS Press, 1993.
    • 6. R.B. Haber and D.A. McNabb, “Visualization Idioms: A Conceptual Model for Scientific Visualization Systems,” Visualization in Scientific Computing, G.M. Nielson, B. Schriver, and L.J. Rosenblum, eds., IEEE CS Press, 1990.
    • 7. L.A. Treinish, “Unifying Principles of Data Management for Scientific Visualization,” Animation and Scientific Visualization, R.A. Earnshaw and D. Watson, eds., Academic Press, 1993, pp. 141-169.
    • 8. P. Grace et al., “GRIDKIT: Pluggable Overlay Networks for Grid Computing,” On the Move to Meaningful Internet Systems 2004, LNCS 3291, R. Meersman and Z. Tari, eds., Springer-Verlag, 2004; http://www.springerlink.com/ index/6QBX3EE75JQXU0MG.
    • 9. M.-C. Rousset, “Small Can Be Beautiful in the Semantic Web,” Proc. 3rd Int'l Semantic Web Conf., S.A. McIlraith et al., eds., Springer-Verlag, 2004, pp. 6-16. Readers may contact David J. Duke at djd@comp.
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