IEEE Trans Vis Comput Graph. 2022 Dec;28(12):5049-5070. doi: 10.1109/TVCG.2021.3099002. Epub 2022 Oct 26.
Visualizations themselves have become a data format. Akin to other data formats such as text and images, visualizations are increasingly created, stored, shared, and (re-)used with artificial intelligence (AI) techniques. In this survey, we probe the underlying vision of formalizing visualizations as an emerging data format and review the recent advance in applying AI techniques to visualization data (AI4VIS). We define visualization data as the digital representations of visualizations in computers and focus on data visualization (e.g., charts and infographics). We build our survey upon a corpus spanning ten different fields in computer science with an eye toward identifying important common interests. Our resulting taxonomy is organized around WHAT is visualization data and its representation, WHY and HOW to apply AI to visualization data. We highlight a set of common tasks that researchers apply to the visualization data and present a detailed discussion of AI approaches developed to accomplish those tasks. Drawing upon our literature review, we discuss several important research questions surrounding the management and exploitation of visualization data, as well as the role of AI in support of those processes. We make the list of surveyed papers and related material available online at.
可视化本身已经成为一种数据格式。类似于文本和图像等其他数据格式，可视化正越来越多地利用人工智能 (AI) 技术进行创建、存储、共享和（重新）使用。在本调查中，我们探讨了将可视化形式化为一种新兴数据格式的基本设想，并回顾了将 AI 技术应用于可视化数据（AI4VIS）的最新进展。我们将可视化数据定义为计算机中可视化的数字表示形式，并专注于数据可视化（例如图表和信息图形）。我们的调查建立在跨越计算机科学十个不同领域的语料库之上，旨在确定重要的共同兴趣。我们的分类法围绕着可视化数据及其表示形式的 WHAT、为何以及如何将 AI 应用于可视化数据展开。我们重点介绍了研究人员应用于可视化数据的一组常见任务，并对为完成这些任务而开发的 AI 方法进行了详细讨论。根据我们的文献综述，我们讨论了围绕可视化数据的管理和利用以及 AI 在支持这些过程中的作用的几个重要研究问题。我们在网上提供了被调查论文和相关材料的列表，网址是。
