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

  • Georges-Pierre BonneauEmail author
  • Hans-Christian Hege
  • Chris R. Johnson
  • Manuel M. Oliveira
  • Kristin Potter
  • Penny Rheingans
  • Thomas Schultz
Part of the Mathematics and Visualization book series (MATHVISUAL)


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.


Visualization Technique Volume Rendering Color Vision Deficiency Uncertainty Information Sybil Attack 
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.



The authors gratefully acknowledge research support from the National Science Foundation, Department of Energy, the National Institutes of Health, and the King Abdullah University for Science and Technology.


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Copyright information

© Springer-Verlag London 2014

Authors and Affiliations

  • Georges-Pierre Bonneau
    • 1
    Email author
  • Hans-Christian Hege
    • 2
  • Chris R. Johnson
    • 3
  • Manuel M. Oliveira
    • 4
  • Kristin Potter
    • 3
  • Penny Rheingans
    • 5
  • Thomas Schultz
    • 6
    • 7
  1. 1.The University of GrenobleGrenobleFrance
  2. 2.Zuse Institute BerlinBerlinGermany
  3. 3.Scientific Computing and Imaging InstituteUniversity of UtahSalt Lake CityUSA
  4. 4.Instituto de InformáticaUFRGSPorto AlegreBrazil
  5. 5.University of Maryland Baltimore CountyBaltimoreUSA
  6. 6.University of BonnBonnGermany
  7. 7.MPI for Intelligent SystemsTübingenGermany

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