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.

中文翻译：

---

曲面可视化海市蜃楼

肮脏的数据和欺骗性的设计实践可能会破坏、颠倒或使图表和图形所声称的信息无效。这些失败可能悄无声息地出现：除非分析师仔细观察并发现支持数据、可视化规范或他们自己的假设存在问题，否则从特定可视化得出的结论可能看起来是合理的。我们将这种无声但重大的失败称为“可视化海市蜃楼”。我们描述了海市蜃楼的概念模型，并展示了如何在可视化分析过程的每个阶段生成海市蜃楼。我们采用了软件测试中的一种方法，即“变形测试”，作为一种通过修改基础数据和图表规范在分析的视觉编码阶段自动呈现潜在海市蜃楼的方法。