HCGRJan 21, 2022

VisQualdex -- the comprehensive guide to good data visualization

arXiv:2201.08684v3
Originality Synthesis-oriented
AI Analysis

This addresses the challenge of misleading or unreadable visualizations in communication, though it appears incremental as it builds on existing frameworks like the Grammar of Graphics.

The authors tackled the problem of low-quality data visualizations by proposing VisQualdex, a systematic set of guidelines for evaluating visualization quality, and made it available as a web server at visqual.info.

The rapid influx of low-quality data visualisations is one of the main challenges in today's communication. Misleading, unreadable, or confusing visualisations spread misinformation, failing to fulfill their purpose. The lack of proper tooling further heightens the problem of the quality assessment process. Therefore, we propose VisQualdex, a systematic set of guidelines isnpired by the Grammar of Graphics for evaluating the quality of data visualisations. To increase the practical impact of VisQualdex, we make these guidelines available in the form of the web server, visqual.info.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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