Collaborating Across Domains and Roles: An Interview Study of Visualization Design Practices
Yiwen Xing, Maria Teresa Ortoleva, Rita Borgo, Alfie Abdul-Rahman
Abstract
Visualization design study is a widely adopted approach for developing tailored visual solutions to domain-specific problems through close interdisciplinary collaboration. While the visualization community has proposed generalizable frameworks, there is a growing need for domain-aware methodologies that address discipline-specific challenges and refine design study practices. To investigate how domain characteristics and collaborator roles influence the design study process, we conducted interviews with 15 experts, including domain specialists from the humanities, arts, applied sciences, and artificial intelligence, as well as visualization researchers and developers, with direct experience in design studies. Our findings reveal tensions and opportunities that arise from differing expectations, communication styles, and levels of engagement among collaborators at various stages of the design process, including problem formulation, co-design, and evaluation. We highlight how domain-specific norms and role dynamics shape collaboration and influence the trajectory of visualization projects. Based on these insights, we offer practical considerations to help visualization researchers anticipate domain-specific challenges, foster mutual understanding, and adapt their methods accordingly. Our study contributes to ongoing efforts to support more context-sensitive, sustainable, and inclusive design study practices across diverse application domains.
Ask about this paper
Ask your agent about it.
Lune has read the top-tier papers around this one, so every answer names the papers it rests on.
Your agent calls
Lunesearch_papers
Free to start. No credit card required.
Terminal
Install the CLIlune papers get c31013fe-96da-4d31-b959-e758a4fbecb4Related papers
- Troubling Collaboration: Matters of Care for Visualization Design StudyDerya Akbaba, Devin Lange, Michael Correll, Alexander Lex et al.CHI 2023 · 41 citations
- Understanding Data Visualization Design PracticePaul ParsonsIEEE VIS 2021 · 53 citations
- Insights From Experiments With Rigor in an EvoBio Design StudyJen Rogers, Austin H. Patton, Luke Harmon, Alexander Lex et al.IEEE VIS 2020 · 28 citations
- Beyond Problem Solving: Framing and Problem-Solution Co-Evolution in Data Visualization DesignPaul C. Parsons, Prakash Chandra ShuklaIEEE VIS 2025 · 5 citations
- Qualitative Study for LLM-assisted Design Study Process: Strategies, Challenges, and RolesShaolun Ruan, Rui Sheng, Xiaolin Wen, Jiachen Wang et al.IEEE VIS 2025 · 2 citations
