Canis: A High-Level Language for Data-Driven Chart Animations
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Date
2020
Journal Title
Journal ISSN
Volume Title
Publisher
The Eurographics Association and John Wiley & Sons Ltd.
Abstract
In this paper, we introduce Canis, a high-level domain-specific language that enables declarative specifications of data-driven chart animations. By leveraging data-enriched SVG charts, its grammar of animations can be applied to the charts created by existing chart construction tools. With Canis, designers can select marks from the charts, partition the selected marks into mark units based on data attributes, and apply animation effects to the mark units, with the control of when the effects start. The Canis compiler automatically synthesizes the Lottie animation JSON files [Aira], which can be rendered natively across multiple platforms. To demonstrate Canis' expressiveness, we present a wide range of chart animations. We also evaluate its scalability by showing the effectiveness of our compiler in reducing the output specification size and comparing its performance on different platforms against D3.
Description
@article{10.1111:cgf.14005,
journal = {Computer Graphics Forum},
title = {{Canis: A High-Level Language for Data-Driven Chart Animations}},
author = {Ge, Tong and Zhao, Yue and Lee, Bongshin and Ren, Donghao and Chen, Baoquan and Wang, Yunhai},
year = {2020},
publisher = {The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {10.1111/cgf.14005}
}