Journal
IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS
Volume 28, Issue 7, Pages 2628-2640Publisher
IEEE COMPUTER SOC
DOI: 10.1109/TVCG.2020.3037300
Keywords
Visualization; Animation; Data visualization; Encoding; Image color analysis; Visual effects; Task analysis; Visual encoding; data-driven; animated effects; charts
Categories
Funding
- NSFC [61802265, 41671387]
- GD Science and Technology Program [2018A030310426, 2020A0505100064, 2015A030312015]
- Guangdong Laboratory of Artificial Intelligence and Digital Economy
- GD Talent Program [2019JC05X328]
- DEGP Key Project [2018KZDXM058, LHTD 20170003]
- National Engineering Laboratory for Big Data System Computing Technology
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This article proposes incorporating data-driven animations into static charts to enhance data encoding and emphasize specific attributes. The impact and effectiveness of the animated effects on visual understanding are evaluated through experiments and user studies.
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 article, 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.
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