Yixuan Zhang, Yifan Sun, Lace Padilla, Sumit Barua, Enrico Bertini, and Andrea G Parker. 2021. Mapping the Landscape of COVID-19 Crisis Visualizations. In Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems (CHI '21). Association for Computing Machinery, New York, NY, USA, Article 608, 1–23. DOI: https://doi.org/10.1145/3411764.3445381
The COVID-19 Pandemic is touching every part of our interconnected world. Its impact is being felt in all parts of our lives. An enormous number of visualizations designed to communicate, understand, analyze, and predict a constantly changing situation are appearing on the Internet every day, created by our biomedical community, health care systems, governments, news media, and the data visualization community at large.
As an initial foray into this research space, we conducted a comprehensive review of 668 COVID-19 visualizations. We present our fndings through a conceptual framework derived from our analysis, that examines who, (uses) what data, (to communicate) what messages, in what form, under what circumstances in the context of COVID-19 crisis visualizations.
We would like to thank many people behind this work, including Ben Shneiderman, Catherine Plaisant, John Stasko, and Alex Endert for discussions and advice; Paul Kahn for co-leading the database at the beginning of the research and people who have facilitated with data collection; as well as Lin Shi, Jennifer Howell, Rumi Chunara, Racquel Fygenson, Helia Hossein-pour, Anamaria Crisan, Hugh Dubberly, Wellness Technology lab at Georgia Tech, Visualization group at Georgia Tech, and VIS lab at Northeastern University for feedback and various levels of support on this work.