2018-vsup.html

---
layout: publication
authors:
  - Michael Correll
  - Dominik Moritz
  - Jeffrey Heer
blog: https://medium.com/@uwdata/value-suppressing-uncertainty-palettes-426130122ce9
doi: 10.1145/3173574.3174216
link: https://github.com/uwdata/vsup
pdf: https://www.domoritz.de/papers/2018-VSUPs-CHI.pdf
short_doi: 10/crpf
tags:
  - Uncertainty
  - Visualization
title: Value-Suppressing Uncertainty Palettes
tweet: Special color palettes that suppress differences for uncertain values.
type:
  - Conference
venue: CHI
venue_location: "Montr\xE9al, Canada"
venue_tags:
  - CHI
venue_url: https://chi2018.acm.org/
year: 2018
---

Understanding uncertainty is critical for many analytical tasks. One common
approach is to encode data values and uncertainty values independently, using
two visual variables. These resulting bivariate maps can be difficult to
interpret, and interference between visual channels can reduce the
discriminability of marks. To address this issue, we contribute
Value-Suppressing Uncertainty Palettes (VSUPs). VSUPs allocate larger ranges of
a visual channel to data when uncertainty is low, and smaller ranges when
uncertainty is high. This non-uniform budgeting of the visual channels makes
more economical use of the limited visual encoding space when uncertainty is
low, and encourages more cautious decisionmaking when uncertainty is high. We
demonstrate several examples of VSUPs, and present a crowdsourced evaluation
showing that, compared to traditional bivariate maps, VSUPs encourage people to
more heavily weight uncertainty information in decision-making tasks.