论文标题
浮出视觉幻影
Surfacing Visualization Mirages
论文作者
论文摘要
肮脏的数据和欺骗性设计实践会破坏，倒置或无效图表和图表的消息。这些失败可能会静静地出现：除非分析师看起来更近，并且发现背景数据，视觉规范或其自己的假设，否则从特定可视化中得出的结论看起来可能是合理的。我们认为如此沉默但重大的故障“可视化幻影”。我们描述了一个概念的幻影模型，并展示了如何在视觉分析过程的每个阶段生成它们。我们从软件测试“变质测试”中调整了一种方法，作为一种在分析的视觉编码阶段自动播放潜在的幻影，通过对基础数据和图表规范进行修改。我们表明，变质测试可以可靠地识别各种图表类型的幻影，而数据或域的先验知识相对较少。
Dirty data and deceptive design practices can undermine, invert, or invalidate the purported messages of charts and graphs. These failures can arise silently: a conclusion derived from a particular visualization may look plausible unless the analyst looks closer and discovers an issue with the backing data, visual specification, or their own assumptions. We term such silent but significant failures "visualization mirages". We describe a conceptual model of mirages and show how they can be generated at every stage of the visual analytics process. We adapt a methodology from software testing, "metamorphic testing", as a way of automatically surfacing potential mirages at the visual encoding stage of analysis through modifications to the underlying data and chart specification. We show that metamorphic testing can reliably identify mirages across a variety of chart types with relatively little prior knowledge of the data or the domain.
