Visualising Temporal Uncertainty: A Taxonomy and Call for Systematic Evaluation
Yashvir S. Grewal, Sarah Goodwin, Tim Dwyer · 2021
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.