ColVis: Collaborative Visualization Design Workshops for Diverse User Groups
This work addresses the problem of integrating interdisciplinary input in data visualization design, but it is incremental as it builds on existing workshop methods without introducing a new paradigm.
The paper tackles the challenge of designing data visualizations for diverse user groups by proposing a collaborative workshop framework that involves both domain experts and novice users, and it provides recommendations based on feedback and reflections from two case studies.
Understanding different types of users' needs can even be more critical in today's data visualization field, as exploratory visualizations for novice users are becoming more widespread with an increasing amount of data sources. The complexity of data-driven projects requires input from including interdisciplinary expert and novice users. Our workshop framework helps taking design decisions collaboratively with experts and novice users, on different levels such as outlining users and goals, identifying tasks, structuring data, and creating data visualization ideas. We conducted workshops for two different data visualization projects. For each project, we conducted a workshop with project stakeholders who are domain experts, then a second workshop with novice users. We collected feedback from participants and used critical reflection on the process. Later on, we created recommendations on how this workshop structure can be used by others. Our main contributions are, (1) the workshop framework for designing data visualizations, (2) describing the outcomes and lessons learned from multiple workshops.