Visualization and Decision Making Design Under Uncertainty

Nadia Boukhelifa, Chris Johnson, Kristin Potter

Research output: Contribution to journalArticlepeer-review


Uncertainty is an important aspect to data understanding. Without awareness of the variability, error, or reliability of a dataset, the ability to make decisions on that data is limited. However, practices around uncertainty visualization remain domain-specific, rooted in convention, and in many instances, absent entirely. Part of the reason for this may be a lack of established guidelines for navigating difficult choices of when uncertainty should be added, how to visualize uncertainty, and how to evaluate its effectiveness. Unsurprisingly, the inclusion of uncertainty into visualizations is a major challenge to visualization. As work concerned with uncertainty visualization grows, it has become clear that simple visual additions of uncertainty information to traditional visualization methods do not appropriately convey the meaning of the uncertainty, pose many perceptual challenges, and, in the worst case, can lead a viewer to a completely wrong understanding of the data. These challenges are the driving motivator for this special issue.
Original languageAmerican English
Pages (from-to)23-25
Number of pages3
JournalIEEE Computer Graphics and Applications
Issue number5
StatePublished - 2023

NREL Publication Number

  • NREL/JA-2C00-87849


  • data models
  • decision making
  • uncertainty
  • visualization


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