Critical Interactivity: Exploration and Narration in Data Visualization
We propose critical interactivity as a concept to study and design the dynamic and transitory aspects of data visualizations. Theoretically, interactivity is often described as the means to support analytical tasks, while in practice, it encompasses the techniques that alter visual representations. These notions are a useful starting point to study the role of interactivity in critical engagements with data visualizations. At the core of critical interactivity is the negotiation of authority and agency: authority as authors provide structure and context, and agency as viewers navigate and interpret the data on their own terms. This raises the critical question: who has the power to control the visualization? Drawing from four case studies in science communication, art history, anthropology, and climate advocacy, we examine how critical interactivity links exploration and narration. We reflect on the effort involved in preparing data and propose design strategies for implementing critical interactivity in data visualization.
Authors
- Francesca Morini (ORCID: https://orcid.org/0000-0002-5677-8175)
- Andrea Scholz (ORCID: https://orcid.org/0000-0001-8822-0355)
- Manuela Garretón (ORCID: https://orcid.org/0000-0003-4626-3984)
- Sabine de Günther (ORCID: https://orcid.org/0000-0001-6936-9381)
- Marian Dörk (ORCID: https://orcid.org/0000-0002-3469-7841)
- Linda Freyberg (ORCID: https://orcid.org/0000-0002-4620-7571)
- Nadia Zeissig
- Fidel Thomet (ORCID: https://orcid.org/0009-0007-0407-0638)
- Ilias Kyriazis (ORCID: https://orcid.org/0000-0001-8958-0168)
- Jona Pomerance
Institutions
- Pontificia Universidad Católica de Chile (CL)
- X-Fab (Germany) (DE)
- University of Applied Sciences Potsdam (DE)
- Prussian Cultural Heritage Foundation (DE)
- Austrian National Library (AT)
- Dissens – Institut für Bildung und Forschung (DE)
- Filmuniversität Babelsberg KONRAD WOLF (DE)
- DIPF | Leibniz Institute for Research and Information in Education (DE)
Publication Details
- Journal
- IEEE Computer Graphics and Applications
- Published
- 2025-04-08
- DOI
- https://doi.org/10.1109/mcg.2025.3544684
- Citations
- 1
- Primary Topic
- Data Visualization and Analytics
- Type
- article
- Field-Weighted Citation Impact
- 1.28