An Autoethnography on Visualization Literacy: A Wicked Measurement Problem

Many components of visualization literacy are represented. One is selected to design a test, bringing the question of the type of visualization type and task to perform.


We contribute an autoethnographic reflection on the complexity of defining and measuring visualization literacy (i.e., the ability to interpret and construct visualizations) to expose our tacit thoughts that often exist in-between polished works and remain unreported in individual research papers. Our work is inspired by the growing number of empirical studies in visualization research that rely on visualization literacy as a basis for developing effective data representations or educational interventions. Researchers have already made various efforts to assess this construct, yet it is often hard to pinpoint either what we want to measure or what we are effectively measuring.

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EduVIS 2025 acceptance “Bridging Educational Theories of Cognitive Load to Visualization Design and Evaluation”

Our workshop paper “Bridging Educational Theories of Cognitive Load to Visualization Design and Evaluation” was accepted at the EduVIS 2025 workshop. I will present this work in Vienna during IEEE VIS week 2025. Continue reading EduVIS 2025 acceptance “Bridging Educational Theories of Cognitive Load to Visualization Design and Evaluation”

PREVis: Perceived Readability Evaluation for Visualizations


Although readability is recognized as an essential quality of data visualizations, so far there has not been a unified definition of the construct in the context of visual representations. As a result, researchers often lack guidance for determining how to ask people to rate their perceived readability of a visualization. To address this issue, we engaged in a rigorous process to develop the first validated instrument targeted at the subjective readability of visual data representations. Our final instrument consists of 11 items across 4 dimensions: understandability, layout clarity, readability of data values, and readability of data patterns.

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