The global fight against the COVID-19 pandemic has presented massive challenges and real opportunities for data science and visualization research and technology. Epidemiologists, virologists, infection control experts and public health officials are required to make sense of information from a huge variety of data sources. Physicians and medical researchers have access to rapidly changing medical data as the pandemic evolves. Political stakeholders (supported by economists, public health officials, and other experts analyzing the data) make decisions on which action to take, balancing the impact on public health with social and economic impacts. The general public is regularly presented with visualization, through news, conventional and social media, and government publications, and these inform their actions for the next days and weeks.

Visualization has played, and continues to play, a key role in the pandemic response. The pandemic has tested all areas of data science more rigorously than ever before, from data collection and analytics through to visualization. The widely varying end users with different tasks and priorities require immediate solutions. Thus, new methods, tools, and methodologies from basic and applied research have been and still are needed. Significant funding has been made available in response to the pandemic for research related to COVID-19. Many researchers in information visualization, and data modelling, in cooperation with end users (epidemiologists, virologists, infection preventionists, economists, and other medical experts) have worked on projects related to the pandemic in multidisciplinary teams.

These unique circumstances mean that novel methodologies and visualization approaches and tools have been developed, extended, and validated with real world data and applications. Much of the time since the initial outbreak has been characterized by emergency response without the time for reflection. Schloss Dagstuhl’s objective to promote the transfer of knowledge between research into informatics and application of informatics, make it an ideal venue to host a seminar focused on consolidating the knowledge gained during the COVID-19 crisis and ensuring that the knowledge is available for those who want to apply it in the ongoing fight against COVID-19 and for future global emergencies.

The purpose of this Dagstuhl Seminar is to bring the visualization community, modelling experts, epidemiologists, infection control experts, and end users together with other application domain experts to reflect on research work done in response to the COVID-19 pandemic. Our goal is to ensure that the lessons and experience of the pandemic are not lost, and that researchers can learn lessons from this pandemic to help address future and contemporary crises, adapting to end user needs for visualization and visual data analysis. The Dagstuhl environment provides an excellent platform for exchange of experiences, often resulting in new collaborations and research ideas. The outcome of this seminar is a book that will answer the following research question:

What are the learnt lessons and experiences of the pandemic in terms of data visualization that will best help the response for future pandemics?

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Daniel Archambault, Fintan McGee, Simone Scheithauer, and Tatiana von Landesberger

• Muna Abu Sin (RKI - Berlin, DE)
• Daniel Archambault (Newcastle University, GB) [dblp]
• Alessio Arleo (TU Eindhoven, NL) [dblp]
• Tom Baumgartl (Universität Köln, DE)
• Rita Borgo (King's College London, GB) [dblp]
• Min Chen (University of Oxford, GB) [dblp]
• Johannes Dreesman (Niedersächsisches Landesgesundheitsamt - Hannover, DE)
• David S. Ebert (University of Oklahoma - Norman, US) [dblp]
• Mohammad Ghoniem (Luxembourg Inst. of Science & Technology, LU) [dblp]
• Andreas Kerren (Linköping University, SE) [dblp]
• Jörn Kohlhammer (Fraunhofer IGD - Darmstadt, DE) [dblp]
• Barbora Kozlíková (Masaryk University - Brno, CZ) [dblp]
• Tatiana Losev (Simon Fraser University - Surrey, CA)
• Biagio Lucini (Swansea University, GB)
• Georgeta Elisabeta Marai (University of Illinois - Chicago, US) [dblp]
• Fintan McGee (Luxembourg Inst. of Science & Technology, LU) [dblp]
• Nicolas Medoc (Luxembourg Inst. of Science & Technology, LU)
• Silvia Miksch (TU Wien, AT) [dblp]
• Kazuo Misue (University of Tsukuba, JP)
• Sibylle Mohr (University of Glasgow, GB)
• Klaus Mueller (Stony Brook University, US) [dblp]
• Mathias Pletz (Universitätsklinikum Jena, DE)
• Huamin Qu (HKUST - Hong Kong, HK) [dblp]
• Nicolas Reinoso-Schiller (Universitätsmedinzin Göttingen, DE)
• Panagiotis Ritsos (Bangor University, GB)
• Roy Ruddle (University of Leeds, GB)
• Holger Scharlach (Niedersächsisches Landesgesundheitsamt - Hannover, DE)
• Simone Scheithauer (Universitätsmedinzin Göttingen, DE)
• Max Sondag (Universität Köln, DE)
• Nikita Srivastava (Universitätsmedinzin Göttingen, DE)
• Cagatay Turkay (University of Warwick - Coventry, GB) [dblp]
• Tatiana von Landesberger (Universität Köln, DE) [dblp]
• Yong Wang (SMU - Singapore, SG)
• Antje Wulff (Universität Oldenburg, DE)
• Michael Wybrow (Monash University - Clayton, AU) [dblp]
• Xiaoru Yuan (Peking University, CN) [dblp]
• Hajo Zeeb (BIPS - Bremen, DE)