Recent advances and challenges in uncertainty visualization: a survey
Recent advances and challenges in uncertainty visualization: a survey
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DOI：
10.1007/s12650-021-00755-1
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发表时间：
2021-05-29
影响因子：
1.7
通讯作者：
Marinier, Robert
中科院分区：
文献类型：
--
作者：
Kamal, Aasim;Dhakal, Parashar;Marinier, Robert
数据随之而来的是不确定性，这是数据科学和分析中普遍而频繁的现象。由于永无止境的技术进步，我们可以获得的信息量呈指数级增长。数据可视化是有效传达该信息的方法之一。由于该错误是数据固有的，因此用户不能在可视化中忽略它。未能在可视化中观察到它可能会导致数据分析师做出有缺陷的决策。数据科学家知道，错过数据可视化中的不确定性可能会导致对数据准确性的误导性结论。在大多数情况下，可视化方法假设表示的信息没有任何错误或不可靠；然而，这很少是正确的。不确定性可视化的目标是尽量减少判断中的误差，尽可能准确地表示信息。这项调查讨论了不确定性可视化的最新方法，以及不确定性的概念及其来源。通过对不确定性可视化文献的研究，我们发现了流行的可视化技术，并指出了它们的优缺点。我们还简要讨论了几种不确定性可视化评估策略。最后，提出了不确定性可视化未来可能的研究方向，并给出了结论。
With data comes uncertainty, which is a widespread and frequent phenomenon in data science and analysis. The amount of information available to us is growing exponentially, owing to never-ending technological advancements. Data visualization is one of the ways to convey that information effectively. Since the error is intrinsic to data, users cannot ignore it in visualization. Failing to observe it in visualization can lead to flawed decision-making by data analysts. Data scientists know that missing out on uncertainty in data visualization can lead to misleading conclusions about data accuracy. In most cases, visualization approaches assume that the information represented is free from any error or unreliability; however, this is rarely true. The goal of uncertainty visualization is to minimize the errors in judgment and represent the information as accurately as possible. This survey discusses state-of-the-art approaches to uncertainty visualization, along with the concept of uncertainty and its sources. From the study of uncertainty visualization literature, we identified popular techniques accompanied by their merits and shortcomings. We also briefly discuss several uncertainty visualization evaluation strategies. Finally, we present possible future research directions in uncertainty visualization, along with the conclusion.