Shi Danqing, Xu Xinyue, Sun Fuling, Shi Yang, Cao Nan
IEEE Trans Vis Comput Graph. 2021 Feb;27(2):453-463. doi: 10.1109/TVCG.2020.3030403. Epub 2021 Jan 28.
Visual data stories shown in the form of narrative visualizations such as a poster or a data video, are frequently used in data-oriented storytelling to facilitate the understanding and memorization of the story content. Although useful, technique barriers, such as data analysis, visualization, and scripting, make the generation of a visual data story difficult. Existing authoring tools rely on users' skills and experiences, which are usually inefficient and still difficult. In this paper, we introduce a novel visual data story generating system, Calliope, which creates visual data stories from an input spreadsheet through an automatic process and facilities the easy revision of the generated story based on an online story editor. Particularly, Calliope incorporates a new logic-oriented Monte Carlo tree search algorithm that explores the data space given by the input spreadsheet to progressively generate story pieces (i.e., data facts) and organize them in a logical order. The importance of data facts is measured based on information theory, and each data fact is visualized in a chart and captioned by an automatically generated description. We evaluate the proposed technique through three example stories, two controlled experiments, and a series of interviews with 10 domain experts. Our evaluation shows that Calliope is beneficial to efficient visual data story generation.
以叙事可视化形式呈现的视觉数据故事，如海报或数据视频，在以数据为导向的叙事中经常被使用，以促进对故事内容的理解和记忆。尽管很有用，但诸如数据分析、可视化和脚本编写等技术障碍使得视觉数据故事的生成变得困难。现有的创作工具依赖于用户的技能和经验，通常效率低下且仍然困难。在本文中，我们介绍了一种新颖的视觉数据故事生成系统Calliope，它通过自动过程从输入的电子表格中创建视觉数据故事，并基于在线故事编辑器方便地对生成的故事进行修订。特别地，Calliope采用了一种新的面向逻辑的蒙特卡洛树搜索算法，该算法探索由输入电子表格给出的数据空间，以逐步生成故事片段（即数据事实）并将它们按逻辑顺序组织起来。数据事实的重要性基于信息论进行衡量，每个数据事实都在图表中可视化，并由自动生成的描述加上标题。我们通过三个示例故事、两个对照实验以及对10位领域专家的一系列访谈来评估所提出的技术。我们的评估表明，Calliope有利于高效的视觉数据故事生成。
