Visualising temporal uncertainty: a taxonomy and call for systematic evaluation

Yashvir Grewal, Sarah Goodwin, Tim Dwyer

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review


Increased reliance on data in decision-making has highlighted the importance of conveying uncertainty in data visualisations. Yet developing visualisation techniques that clearly and accurately convey uncertainty in data is an open challenge across a variety of fields. This is especially the case when visualising temporal uncertainty. To facilitate the development of innovative and accessible temporal uncertainty visualisation techniques and respond to an identified gap in the literature, we propose the first-ever survey of over 50 temporal uncertainty visualisation techniques deployed in numerous fields. Our paper offers two contributions. First, we propose a novel taxonomy to be applied when classifying temporal uncertainty visualisation techniques. This takes into account the visualisation's intended audience, as well as its level of discreteness in representing uncertainty. Second, we urge researchers and practitioners to use a greater variety of visualisations which differ in terms of their discreteness. In doing so, we believe that a more robust evaluation of visualisation techniques can be achieved.

Original languageEnglish
Title of host publicationProceedings - 2021 IEEE 14th Pacific Visualization Symposium PacificVis 2021
EditorsNan Cao, Holger Theisel, Chaoli Wang
Place of PublicationPiscataway NJ USA
PublisherIEEE, Institute of Electrical and Electronics Engineers
Number of pages5
ISBN (Electronic)9781665439312
ISBN (Print)9781665439329
Publication statusPublished - 2021
EventIEEE Pacific Visualization Symposium 2021 - Virtual, Tianjin, China
Duration: 19 Apr 202121 Apr 2021
Conference number: 14 (Website) (Proceedings)

Publication series

Name2021 IEEE 14th Pacific Visualization Symposium
PublisherThe Institute of Electrical and Electronics Engineers, Inc.
ISSN (Print)2165-8765
ISSN (Electronic)2165-8773


ConferenceIEEE Pacific Visualization Symposium 2021
Abbreviated titlePacificVis 2021
Internet address


  • Human-centered computing
  • Uncertainty
  • Visualization
  • Visualization techniques

Cite this