Overview and state-of-the-art of uncertainty visualization

被引:1
作者
Bonneau, Georges-Pierre [1 ]
Hege, Hans-Christian [2 ]
Johnson, Chris R. [3 ]
Oliveira, Manuel M. [4 ]
Potter, Kristin [3 ]
Rheingans, Penny [5 ]
Schultz, Thomas [6 ,7 ]
机构
[1] The University of Grenoble, Grenoble
[2] Zuse Institute Berlin, Berlin
[3] Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, UT
[4] Instituto de Informática, UFRGS, Porto Alegre, RS
[5] University of Maryland Baltimore County, Baltimore, MD
[6] University of Bonn, Bonn
[7] MPI for Intelligent Systems, Tübingen
来源
Mathematics and Visualization | 2014年 / 37卷
基金
美国国家科学基金会; 美国国家卫生研究院;
关键词
Decision making - Data visualization - Uncertainty analysis;
D O I
10.1007/978-1-4471-6497-5_1
中图分类号
学科分类号
摘要
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. © Springer-Verlag London 2014.
引用
收藏
页码:3 / 27
页数:24
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