Summary
In this position paper we argue that improving visualization literacy evaluation tools is important for defining and understanding the concept of readability in data visualizations.
Only with reliable and relevant measures can we assess how a potential factor affects a reader’s performance; accordingly, only with appropriate measuring instruments can we start to investigate the tight web of interactions between individual characteristics, features of the visual design, and reading tasks requirements. As we slowly progress in our understanding of how people process information from data visualization, and based on these improved tools and other developments, we can further develop theoretical foundations in data visualization.
This position paper was accepted at ACM CHI24 Workshop: Toward a More Comprehensive Understanding of Visualization Literacy.
Anne-Flore Cabouat, Tingying He, Florent Cabric, Tobias Isenberg, and Petra Isenberg. 2024. Position paper: A case to study the relationship between data visualization readability and visualization literacy. In CHI ’24 Workshop: Toward a More Comprehensive Understanding of Visualization Literacy. ACM, New York, NY, USA, 10 pages. https://hal.science/hal-04523790
A triadic reciprocal representation of components influencing reading task performance in data visualization.
The authors created this figure and share it under the CC BY 4.0 license.