Sociotechnical Considerations for Accessible Visualization Design
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Abstract (arXiv)
Accessibility--the process of designing for people with disabilities (PWD)--is an important but under-explored challenge in the visualization research community. Without careful attention, and if PWD are not included as equal participants throughout the process, there is a danger of perpetuating a vision-first approach to accessible design that marginalizes the lived experience of disability (e.g., by creating overly simplistic "sensory translations" that map visual to non-visual modalities in a one-to-one fashion). In this paper, we present a set of sociotechnical considerations for research in accessible visualization design, drawing on literature in disability studies, tactile information systems, and participatory methods. We identify that using state-of-the-art technologies may introduce more barriers to access than they remove, and that expectations of research novelty may not produce outcomes well-aligned with the needs of disability communities. Instead, to promote a more inclusive design process, we emphasize the importance of clearly communicating goals, following existing accessibility guidelines, and treating PWD as equal participants who are compensated for their specialized skills. To illustrate how these considerations can be applied in practice, we discuss a case study of an inclusive design workshop held in collaboration with the Perkins School for the Blind.
Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). First posted on arXiv 11 Sep 2019.
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Citing papers per year: 2021: 1; 2022: 0; 2023: 0; 2024: 0; 2025: 1; 2026: 3.
5 papers.
- 2021Accessible Visualization via Natural Language Descriptions: A Four-Level Model of Semantic Contentcited by 39
- 2025A Review on Large Language Models for Visual Analyticscited by 1
- 2026Three Modalities, Two Design Probes, One Prototype, and No Vision: Experience-Based Co-Design of a Multi-modal 3D Data Visualization Toolcited by 1
- 2026Now You See Me: Designing Responsible AI Dashboards for Early-Stage Health Innovationcited by 0
- 2026Skeleton: Visual Authoring of Non-visual Data Experiencescited by 0
- 2026Skeleton: Visual Authoring of Non-visual Data Experiences16 Jul 2026
- 2026Three Modalities, Two Design Probes, One Prototype, and No Vision: Experience-Based Co-Design of a Multi-modal 3D Data Visualization Tool10 Apr 2026
- 2026Now You See Me: Designing Responsible AI Dashboards for Early-Stage Health Innovation27 Jan 2026
- 2025A Review on Large Language Models for Visual Analytics19 Mar 2025
- 2021Accessible Visualization via Natural Language Descriptions: A Four-Level Model of Semantic Content8 Oct 2021