Browsing by Author "Zhang, Dongmei"

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    Animated Presentation of Static Infographics with InfoMotion
    (The Eurographics Association and John Wiley & Sons Ltd., 2021) Wang, Yun; Gao, Yi; Huang, Ray; Cui, Weiwei; Zhang, Haidong; Zhang, Dongmei; Borgo, Rita and Marai, G. Elisabeta and Landesberger, Tatiana von
    By displaying visual elements logically in temporal order, animated infographics can help readers better understand layers of information expressed in an infographic. While many techniques and tools target the quick generation of static infographics, few support animation designs. We propose InfoMotion that automatically generates animated presentations of static infographics. We first conduct a survey to explore the design space of animated infographics. Based on this survey, InfoMotion extracts graphical properties of an infographic to analyze the underlying information structures; then, animation effects are applied to the visual elements in the infographic in temporal order to present the infographic. The generated animations can be used in data videos or presentations. We demonstrate the utility of InfoMotion with two example applications, including mixed-initiative animation authoring and animation recommendation. To further understand the quality of the generated animations, we conduct a user study to gather subjective feedback on the animations generated by InfoMotion.
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    Investigating the Role and Interplay of Narrations and Animations in Data Videos
    (The Eurographics Association and John Wiley & Sons Ltd., 2022) Cheng, Hao; Wang, Junhong; Wang, Yun; Lee, Bongshin; Zhang, Haidong; Zhang, Dongmei; Borgo, Rita; Marai, G. Elisabeta; Schreck, Tobias
    Combining data visualizations, animations, and audio narrations, data videos can increase viewer engagement and effectively communicate data stories. Due to their increasing popularity, data videos have gained growing attention from the visualization research community. However, recent research on data videos has focused on animations, lacking an understanding of narrations. In this work, we study how data videos use narrations and animations to convey information effectively. We conduct a qualitative analysis on 426 clips with visualizations extracted from 60 data videos collected from a variety of media outlets, covering a diverse array of topics. We manually label 816 sentences with 1226 semantic labels and record the composition of 2553 animations through an open coding process. We also analyze how narrations and animations coordinate with each other by assigning links between semantic labels and animations. With 937 (76.4%) semantic labels and 2503 (98.0%) animations linked, we identify four types of narration-animation relationships in the collected clips. Drawing from the findings, we discuss study implications and future research opportunities of data videos.