Christopher G. Healey - Designing a visualization framework for

Journal article

B. Dennis, S. Kocherlakota, A. P. Sawant, L. Tateosian, C. G. Healey
IEEE Computer Graphics & Applications, vol. 25(6), 2005, pp. 10-15

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APA Click to copy
Dennis, B., Kocherlakota, S., Sawant, A. P., Tateosian, L., & Healey, C. G. (2005). Designing a visualization framework for multidimensional data. IEEE Computer Graphics &Amp; Applications, 25(6), 10–15.

Chicago/Turabian Click to copy
Dennis, B., S. Kocherlakota, A. P. Sawant, L. Tateosian, and C. G. Healey. “Designing a Visualization Framework for Multidimensional Data.” IEEE Computer Graphics & Applications 25, no. 6 (2005): 10–15.

MLA Click to copy
Dennis, B., et al. “Designing a Visualization Framework for Multidimensional Data.” IEEE Computer Graphics &Amp; Applications, vol. 25, no. 6, 2005, pp. 10–15.

BibTeX Click to copy

@article{b2005a,
  title = {Designing a visualization framework for multidimensional data},
  year = {2005},
  issue = {6},
  journal = {IEEE Computer Graphics & Applications},
  pages = {10-15},
  volume = {25},
  author = {Dennis, B. and Kocherlakota, S. and Sawant, A. P. and Tateosian, L. and Healey, C. G.}
}

Abstract

Interest in visualization has grown in recent years, producing rapid advances in the diversity of research and in the scope of proposed techniques. Much of the initial focus in computer-based visualization concentrated on display algorithms, often for specific domains. For example, volume, flow, and terrain visualization techniques have generated significant insights into fundamental graphics and visualization theory, aiding the application experts who use these techniques to advance their own research. More recent work has extended visualization to abstract data sets like network intrusion detection, recommender systems, and database query results. This article describes our initial end-to-end system that starts with data management and continues through assisted visualization design, display, navigation, and user interaction. The purposes of this discussion are to (i) promote a more comprehensive visualization framework; (ii) describe how to apply expertise from human psychophysics, databases, rational logic, and artificial intelligence to visualization; and (iii) illustrate the benefits of a more complete framework using examples from our own experiences.