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. We define visualization data as the digital representations of visualizations in computers and focus on visualizations in information visualization and visual analytic. 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 ai4vis.github.io.

中文翻译：

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可视化数据的人工智能方法概述

可视化本身已成为一种数据格式。类似于其他数据格式（例如文本和图像），可视化越来越多地通过人工智能（AI）技术创建，存储，共享和（重新）使用。在这项调查中，我们探讨了将可视化形式规范化为新兴数据格式的基本愿景，并回顾了将AI技术应用于可视化数据领域的最新进展。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，并专注于信息可视化和可视化分析中的可视化。我们基于涵盖计算机科学十个不同领域的语料库进行调查，以期确定重要的共同兴趣。我们得出的分类法是围绕可视化数据及其表示形式，为什么和如何将AI应用于可视化数据进行组织的。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，并详细讨论了为完成这些任务而开发的AI方法。利用我们的文献综述，我们讨论了有关可视化数据管理和开发的几个重要研究问题，以及AI在支持这些过程中的作用。我们可以在ai4vis.github.io在线获取被调查论文和相关材料的列表。