Designed co-design sessions for 9 participants using visual and non-verbal methods suited to their communication needs.
2
Run co-design and testing
Combined generative methods (interviews and co-design) with evaluative methods (usability testing) across workshops.
3
Collect ratings and surveys
Gathered survey and rating data alongside qualitative observations.
4
Synthesise
Used journey mapping and Framework Analysis to turn co-design data into clear findings and accessibility barriers.
5
Share
Presented through workshops, conference talks and journal papers, and maintain the project website.
The question
Data visualisation is everywhere, from health information to news, but most design guidance assumes readers can easily process text-heavy labels, legends and explanations. This project explores how people with aphasia and developmental language disorder (DLD) experience data visualisation, and what would make charts work better for them.
Approach
Working with colleagues in an interdisciplinary team, I set up and run workshops where participants co-design visualisation approaches with us. Methods are adapted to participants' communication needs, relying on visual and non-verbal techniques rather than long verbal explanations.
Project publications
Publications from the project team. More are listed on the project website.
Karkanevatos, A., Wood, J., Botting, N., Cruice, M., Devane, N., Octaviani, U., Roper, A. and Wilson, S., 2026. Supporting Focus in Data Visualization Design: Lessons Learned from People with Language Disabilities. Proceedings of EuroVis 2026.
Accessibility and Experience of Data Visualization for Adults with Language Disability. International Aphasia Rehabilitation Conference (IARC) 2026, abstract. Read the abstract
Wood, J., Devane, N., Roper, A., Botting, N., Cruice, M., Octaviani, U. and Wilson, S., 2025. Experiencing Data Visualization with Language Disability. IEEE Computer Graphics and Applications. doi:10.1109/mcg.2025.3642747
Data Visualization Experiences of People with Language Disability, a Qualitative Study. Computer Graphics and Visual Computing (CGVC) 2024. Read the paper