Bad for Data, Good for the Brain : Knowledge-First Axioms For Visualization Design
Bad for Data, Good for the Brain : Knowledge-First Axioms For Visualization Design
复制标题
对数据不利，对大脑有利：可视化设计的知识优先公理
DOI：
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发表时间：
2014
期刊：
影响因子：
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通讯作者：
Michael Gleicher
中科院分区：
文献类型：
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作者：
M. Correll;Michael Gleicher
传统上，可视化设计假设可视化的有效性是基于呈现数据的数量和清晰度。我们认为，可视化需要一个更细致入微的视角。数据本身并不是目的，而是达到目的的手段（如产生知识或协助决策）。专注于数据本身的呈现可能会导致这些更高目标被忽视的情况。在认知或知觉偏见使“仅仅”数据的呈现与故意歪曲一样具有误导性的情况下，情况尤其如此。我们认为，我们需要去神圣化的数据，并偶尔促进设计扭曲或模糊的数据，以服务于理解。我们讨论了有益的修饰，失真和模糊的可视化的例子，并认为这些例子是一个更广泛的一类技术的代表超越简单的数据表示。
Traditionally, visualization design assumes that the e↵ectiveness of visualizations is based on how much, and how clearly, data are presented. We argue that visualization requires a more nuanced perspective. Data are not ends in themselves, but means to an end (such as generating knowledge or assisting in decision-making). Focusing on the presentation of data per se can result in situations where these higher goals are ignored. This is especially the case for situations where cognitive or perceptual biases make the presentation of “just” the data as misleading as willful distortion. We argue that we need to de-sanctify data, and occasionally promote designs which distort or obscure data in service of understanding. We discuss examples of beneficial embellishment, distortion, and obfuscation in visualization, and argue that these examples are representative of a wider class of techniques for going beyond simplistic presentations of data.