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Overview and State-of-the-Art of Uncertainty Visualization

Abstract : The goal of visualization is to effectively and accurately communicate data. Visualization research has often overlooked the errors and uncertainty which accompany the scientific process and describe key characteristics used to fully understand the data. The lack of these representations can be attributed, in part, to the inherent difficulty in defining, characterizing, and controlling this uncertainty, and in part, to the difficulty in including additional visual metaphors in a well designed, potent display. However, the exclusion of this information cripples the use of visualization as a decision making tool due to the fact that the display is no longer a true representation of the data. This systematic omission of uncertainty commands fundamental research within the visualization community to address, integrate, and expect uncertainty information. In this chapter, we outline sources and models of uncertainty, give an overview of the state-of-the-art, provide general guidelines, outline small exemplary applications, and finally, discuss open problems in uncertainty visualization.
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Contributor : Georges-Pierre Bonneau Connect in order to contact the contributor
Submitted on : Wednesday, September 3, 2014 - 4:14:52 PM
Last modification on : Friday, November 18, 2022 - 9:24:34 AM



Georges-Pierre Bonneau, Hans-Christian Hege, Chris Johnson, Manuel M. Oliveira, Kristin Potter, et al.. Overview and State-of-the-Art of Uncertainty Visualization. Hansen, Charles and Chen, Min and Johnson, Chris and Kaufman, Arie and Hagen, Hans. Scientific Visualization: Uncertainty, Multifield, Biomedical, Scalable, 17, Springer, pp.3-27, 2014, Mathematics and Visualization, 978-1-4471-6496-8. ⟨10.1007/978-1-4471-6497-5_1⟩. ⟨hal-01060465⟩



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