The trouble with data is that often it provides only an imperfect representation of the phenomenon of interest. When reading and interpreting data, personal knowledge about the data plays an important role. Data visualization, however, has neither a concept defining personal knowledge about datasets, nor the methods or tools to robustly integrate them into an analysis process, thus hampering analysts' ability to express their personal knowledge about datasets, and others to learn from such knowledge. In this work, we define such personal knowledge about datasets as data hunches and elevate this knowledge to another form of data that can be externalized, visualized, and used for collaboration. We establish the implications of data hunches and provide a design space for externalizing and communicating data hunches through visualization techniques. We envision such a design space will empower users to externalize their personal knowledge and support the ability to learn from others' data hunches.

中文翻译：

---

数据预感：将个人知识融入可视化

数据的问题在于，它通常只能对感兴趣的现象提供不完美的表示。在阅读和解释数据时，有关数据的个人知识起着重要作用。然而，数据可视化既没有定义关于数据集的个人知识的概念，也没有将它们稳健地集成到分析过程中的方法或工具，从而阻碍了分析师表达他们关于数据集的个人知识以及其他人从这些知识中学习的能力。在这项工作中，我们将关于数据集的此类个人知识定义为数据预感，并将这些知识提升为另一种可以外化、可视化和用于协作的数据形式。我们建立了数据预感的含义，并提供了一个设计空间，通过可视化技术将数据预感外化和交流。我们设想这样的设计空间将使用户能够将他们的个人知识外化，并支持从他人的数据预感中学习的能力。