可视化时间不确定性:一个分类和对系统评估的呼吁

Yashvir S. Grewal, Sarah Goodwin, Tim Dwyer
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引用次数: 1

摘要

决策过程中对数据依赖的增加凸显了在数据可视化中传达不确定性的重要性。然而,开发能够清晰、准确地传达数据不确定性的可视化技术,在各个领域都是一个公开的挑战。在可视化时间不确定性时尤其如此。为了促进创新和可获取的时间不确定性可视化技术的发展,并回应文献中已确定的差距,我们提出了对50多种时间不确定性可视化技术的首次调查,这些技术应用于许多领域。我们的论文提供了两个贡献。首先,我们提出了一种新的分类法,用于对时间不确定性可视化技术进行分类。这要考虑到可视化的目标受众,以及它在表示不确定性时的离散程度。其次,我们敦促研究人员和实践者使用更多种类的可视化,这些可视化在离散性方面有所不同。通过这样做,我们相信可以实现对可视化技术的更可靠的评估。
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Visualising Temporal Uncertainty: A Taxonomy and Call for Systematic Evaluation
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.
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