Workshop papers

Readability as a multi-measure construct in data visualization

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In this paper, we argue that readability cannot be meaningfully discussed without considering multiple complementary measures, and that relying on a single measure constitutes an epistemological choice that constrains the conclusions that can be drawn.

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A case to study the relationship between data visualization readability and visualization literacy (position paper)

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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.

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Open Questions about the Visualization of Sociodemographic Data

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Triangle with "Efficiency", "Inclusiveness" and "Simplicity" as summits, representing the trade-offs for visualization of sociodemographic data.

The visualization research community engaged a reflection on how to represent data about people. This work collects a set of open research questions and highlights some future research directions.

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Florent Cabric, Margrét Vilborg Bjarnadóttir, Anne-Flore Cabouat, and Petra Isenberg. Open Questions about the Visualization of Sociodemographic Data. In Workshop on Visualization for Social Good (VIS4Good). IEEE. 2023.

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