VizLinter: A Linter and Fixer Framework for Data Visualization

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Qing Chen, Fuling Sun, Xinyue Xu, Zui Chen, Jiazhe Wang, Nan Cao

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 View presentation:2021-10-27T18:15:00ZGMT-0600Change your timezone on the schedule page
2021-10-27T18:15:00Z

Exemplar figure, described by caption below — VizLinter is a linter and fixer framework for data visualization. It can help detect problems in a given defective visualization and correct them. The framework consists of two components, a linter and a fixer. The linter inspects the legitimacy of a visualization against well-established design principles, and the fixer automatically resolves the violations detected by the linter.

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Abstract

Despite the rising popularity of automated visualization tools, existing systems tend to provide direct results which do not always fit the input data or meet visualization requirements. Therefore, additional specification adjustments are still required in real-world use cases. However, manual adjustments are difficult since most users do not necessarily possess adequate skills or visualization knowledge. Even experienced users might create imperfect visualizations that involve chart construction errors. We present a framework, VizFixer, to help users detect flaws and rectify already-built but defective visualizations. The framework consists of two components, (1) a visualization linter, which applies well-recognized principles to inspect the legitimacy of rendered visualizations, and (2) a visualization fixer, which automatically corrects the detected violations according to the linter. We implement the framework into an online editor prototype based on Vega-Lite specifications. To further evaluate the system, we conduct an in-lab user study. The results prove its effectiveness and efficiency in identifying and fixing errors for data visualizations.