Sun Mengdi, Cai Ligan, Cui Weiwei, Wu Yanqiu, Shi Yang, Cao Nan
IEEE Trans Vis Comput Graph. 2023 Jan;29(1):983-993. doi: 10.1109/TVCG.2022.3209428. Epub 2022 Dec 16.
As an effective form of narrative visualization, visual data stories are widely used in data-driven storytelling to communicate complex insights and support data understanding. Although important, they are difficult to create, as a variety of interdisciplinary skills, such as data analysis and design, are required. In this work, we introduce Erato, a human-machine cooperative data story editing system, which allows users to generate insightful and fluent data stories together with the computer. Specifically, Erato only requires a number of keyframes provided by the user to briefly describe the topic and structure of a data story. Meanwhile, our system leverages a novel interpolation algorithm to help users insert intermediate frames between the keyframes to smooth the transition. We evaluated the effectiveness and usefulness of the Erato system via a series of evaluations including a Turing test, a controlled user study, a performance validation, and interviews with three expert users. The evaluation results showed that the proposed interpolation technique was able to generate coherent story content and help users create data stories more efficiently.
作为一种有效的叙事可视化形式，视觉数据故事在数据驱动的叙事中被广泛应用，以传达复杂的见解并支持对数据的理解。尽管它们很重要，但却难以创建，因为需要多种跨学科技能，如数据分析和设计。在这项工作中，我们介绍了Erato，一个人机协作的数据故事编辑系统，它允许用户与计算机一起生成有洞察力且流畅的数据故事。具体而言，Erato只需要用户提供一些关键帧来简要描述数据故事的主题和结构。同时，我们的系统利用一种新颖的插值算法来帮助用户在关键帧之间插入中间帧，以使过渡更加平滑。我们通过一系列评估，包括图灵测试、受控用户研究、性能验证以及与三位专家用户的访谈，对Erato系统的有效性和实用性进行了评估。评估结果表明，所提出的插值技术能够生成连贯的故事内容，并帮助用户更高效地创建数据故事。
