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dc.contributor.authorGe, Tongen_US
dc.contributor.authorZhao, Yueen_US
dc.contributor.authorLee, Bongshinen_US
dc.contributor.authorRen, Donghaoen_US
dc.contributor.authorChen, Baoquanen_US
dc.contributor.authorWang, Yunhaien_US
dc.contributor.editorViola, Ivan and Gleicher, Michael and Landesberger von Antburg, Tatianaen_US
dc.description.abstractIn 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.en_US
dc.publisherThe Eurographics Association and John Wiley & Sons Ltd.en_US
dc.rightsAttribution 4.0 International License
dc.subjectHuman centered computing
dc.subjectVisualization toolkits
dc.subjectInformation visualization
dc.subjectVisualization systems and tools
dc.titleCanis: A High-Level Language for Data-Driven Chart Animationsen_US
dc.description.seriesinformationComputer Graphics Forum
dc.description.sectionheadersGraphs and Charts

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  • 39-Issue 3
    EuroVis 2020 - Conference Proceedings

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Attribution 4.0 International License
Except where otherwise noted, this item's license is described as Attribution 4.0 International License