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Visualising Temporal Uncertainty: A Taxonomy and Call for Systematic Evaluation

机译:可视化时间不确定性:分类法并呼叫系统评估

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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.
机译:增加决策中数据的依赖突出了传送数据在数据等待中的不确定性的重要性。然而,开发可视化技术,清楚准确地传达数据中的不确定性是各种领域的开放挑战。在可视化时间不确定性时,尤其如此。为了促进创新和可访问的时间不确定性可视化技术,并回应文献中的识别差距,我们提出了对多个领域部署的50多个时间不确定性可视化技术的第一次调查。我们的论文提供了两项贡献。首先,我们提出了在分类时间不确定性可视化技术时应用新的分类法。这考虑了可视化的预期观众,以及代表不确定性的离散程度。其次,我们敦促研究人员和从业者使用各种各样的可视化,这在离散性方面不同。在这样做时,我们认为可以实现对可视化技术的更强大的评估。

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