Enhancing Static Charts with Data-driven Animations

IEEE Transactions on Visualization and Computer Graphics 2021

Min Lu1    Noa Fish2    Shuaiqi Wang1    Joel Lanir3    Daniel Cohen-Or2    Hui Huang1*

1Shenzhen University    2Tel Aviv University    3THe University of Haifa

Fig. 1. Adding animated cues to Playfair’s Visualization: moving ’$’ symbols are added over the bars. Their speed is mapped to the ratio of wage to wheat price. The faster moving ’$’ signs in 18th century strengthens Playfair’s statement that "never at any former period was wheat so cheap, in proportion to mechanical labour, as it is at the present time".
Fig. 2. Categorization of Data-driven Animations: examples of existing works or techniques are shown in the corresponding cells.


Static visual attributes such as color and shape are used with great success in visual charts designed to be displayed in static, hard-copy form. However, nowadays digital displays become ubiquitous in the visualization of any form of data, lifting the confines of static presentations. In this work, we propose incorporating data-driven animations to bring static charts to life, with the purpose of encoding and emphasizing certain attributes of the data. We lay out a design space for data-driven animated effects and experiment with three versatile effects, marching ants, geometry deformation and gradual appearance. For each, we provide practical details regarding their mode of operation and extent of interaction with existing visual encodings. We examine the impact and effectiveness of our enhancements through an empirical user study to assess preference as well as gauge the influence of animated effects on human perception in terms of speed and accuracy of visual understanding.

Fig. 3. Data-driven Animated Visual Effect: modelled as the visual encoding of a visual proxy, transforming its visual variable dynamically to represent certain data.
Fig. 4. Marching Ants: a Marching Ants effect is determined by five design components, which can be encoded to indicate numerical, directional and semantic messages.

Fig. 5. Variation of Marching Ants: with various choices in design, Marching Ants demonstrates a rich expressive potential. Note that the arrows in handdrawn style are markers to hint the animated effect due to the hard-print manuscript.
Fig. 7. Variation of Geometry Deformation: different design choices of context preservation and extent of bandwidth and speed, when enhancing the existence of cliques and their magnitude in a node-link diagram and matrix.

Fig. 10. Charts enhanced with animated effects: (a) MA driven by numerical attributes; boxplot (top), circos (bottom). (b) GD driven by the spatial structure of the data in the graph visualizations; node-link diagram (top), matrix (bottom) (c) GA driven by the hierarchy of the data in the tree visualizations; circle packing (top), treemap (bottom). Here the animated effects are represented by static cues in hand-drawn style (e.g., arrows). To view the original animated version, please visit the project homepage.

Data & Code

Note that the DATA and CODE are free for Research and Education Use ONLY. 

Please cite our paper (add the bibtex below) if you use any part of our ALGORITHM, CODE, DATA or RESULTS in any publication.

Code: https://github.com/vizgroup/DynamicEffect


We would like to thank the reviewers for their valuable comments. This work is supported in parts by NSFC (61802265, 41671387, 61761146002, 61861130365), LHTD (20170003), Guangdong Provincial Natural Science Foundation (2018A030310426, 2015A030312015), and the National Engineering Laboratory for Big Data System Computing Technology.

title = {Enhancing Static Charts with Data-driven Animations
author = {Min Lu and Noa Fish and Shuaiqi Wang and Joel Lanir and Daniel Cohen-Or and Hui Huang},
journal = {IEEE Transactions on Visualization and Computer Graphics},
volumn = {},  
number = {},  
pages = {},  
year = {2021},

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