Talk Title:  Rethinking One-Size-Fits-All: Designing Cognitively Accessible Visualizations

Speaker:  Keke Wu, Assistant Professor, College of Information, University of Maryland ; Director of the Lived Data Collective ; Associate Director of MIDA

Location: IRB 4105 and Zoom

Abstract:  Data visualization amplifies cognition and broadens access to information. Yet most visualizations are designed with a narrow audience in mind, assuming users who are analytically driven, highly data-literate, and comfortable with abstract representations. This approach excludes many, particularly those with cognitive disabilities, who may struggle with abstraction, experience sensory overload, or have limited exposure to statistical conventions. Working with individuals with Intellectual and Developmental Disabilities (IDD), my research has uncovered both the limitations and possibilities of visualization. Through graphical perception studies, interviews, and co-design, I have examined how people with IDD interpret visualizations, engage with data in daily life, and create their own data representations. These insights inform practical design guidelines while demonstrating the broader potential of visualization as a tool for self-expression, advocacy, and more inclusive data engagement beyond traditional charts and analysis. Building on this foundation, I will outline a vision for a more accessible, expressive, and inclusive future of visualization.

Bio: Keke Wu is an Assistant Professor in the College of Information at the University of Maryland, where she directs the Lived Data Collective and serves as an Associate Director of MIDA. A researcher and storyteller, she bridges data and lived experience through visualization. Her collaborations with individuals with intellectual and developmental disabilities helped establish the subfield of cognitively accessible visualization and continue to fuel her passion for making data more understandable, expressive, and meaningful across diverse audiences and contexts. With a background in Computer Science, Cinematic Arts, and Creative Technology & Design, she integrates storytelling, aesthetics, and computing to advance cognitive accessibility, foster emotional connection, and create social impact through data. Her work has been published in venues including ACM CHI, IEEE VIS, and ACM ASSETS, and was recognized with a Best Paper Award at CHI 2021 for contributions to inclusive visualization.