Anne-Flore Cabouat I presented my Ph.D. topic at the LISN Ph.D. day 2025 in Université Paris-Saclay in Orsay. Continue reading LISN Ph.D. days 2025 presentation
I presented my work for the i3 Doctoriales 2025 in École des Mines de Paris. Continue reading Doctoriales 2025 i3 presentation
Our short paper “We should change how we measure user experience in visual analytics systems” was accepted at EuroVA workshop 2025. Eliane Zambon Victorelli will present it at EuroVis 2025. Continue reading EuroVA 2025 acceptance “We should change how we measure user experience in visual analytics systems”
I visited the Visualization Research Center in Stuttgart with Petra Isenberg.
I presented our work on PREVis to the team there.
I presented our paper “PREVis: Perceived Readability Evaluation for Visualizations” at IEEE Visualization 2024 (online).
[icon name="trophy" prefix="fas"] This work received a Best Paper Honorable Mention Award. Continue reading PREVis paper at VIS 2024 (online)
I started my PhD to explore readability in data visualization in the Aviz group, under the supervision of Petra Isenberg (Inria, LISN, Université Paris-Saclay) and Samuel Huron (Telecom Paris, Institut Polytechnique de Paris, CNRS i3). Continue reading Starting my PhD
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.
Visual representations of data are increasingly prevalent, but we lack a detailed theoretical framework to explain what factors make easy or difficult to read and understand; nor do we know how such factors can impact data visualizations’ efficiency as learning material.
In this Master’s Thesis, I address this gap by exploring the validity and applicability of Cognitive Load Theory, an educational and cognitive science theoretical framework, for designing and evaluating data visualizations. Beyond empirical findings, I also contribute an interdisciplinary perspective on the cognitive processing of visualizations, and I discuss implications in assessing readability in visualization studies.
Continue reading A cognitive load approach to designing and evaluating data visualizationsI presented our position paper “A case to study the relationship between data visualization readability and visualization literacy” remotely at the Workshop: Toward a More Comprehensive Understanding of Visualization Literacy @CHI24 and in person at the para.CHI’24 Paris event. Continue reading Position paper at CHI Workshop on Visualization Literacy
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.
Continue reading A case to study the relationship between data visualization readability and visualization literacy (position paper)I started a follow-up 6 months internship at the Aviz group under the supervision of Tobias Isenberg (Université Paris-Saclay, CNRS, Inria, LISN) to complete the development of a scale to assess perceived readability in data visualization. Continue reading Starting my M2 internship
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.
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.
Continue reading Open Questions about the Visualization of Sociodemographic Data
We draw from the cognitive psychology literature on models of reading text, and describe a knowledge gap for cognitive processes at work when reading visual representations of data.
Continue reading Pondering the reading of visual representationsI started a 6 months internship at the Aviz group under the supervision of Tobias Isenberg (Université Paris-Saclay, CNRS, Inria, LISN). Continue reading Starting M1 internship