@article{674,
  keywords = {Visualization, Visual analytics, Pandemics, COVID-19, SARS-CoV-2},
  author = {Tom Baumgartl and Mohammad Ghoniem and Tatiana von Landesberger and G Elisabeta Marai and Silvia Miksch and Sibylle Mohr and Simone Scheithauer and Nikita Srivastava},
  title = {Empowering Communities: Tailored Pandemic Data Visualization for Varied Tasks and Users},
  abstract = {<p>Data visualization methodologies were intensively leveraged during the COVID-19 pandemic. We review our design experience working on a set of interdisciplinary COVID-19 pandemic projects. We describe the challenges we met in these projects, characterize the respective user communities, the goals and tasks we supported, and the data types and visual media we worked with. Furthermore, we instantiate these characterizations in a series of case studies. Finally, we describe the visual analysis lessons we learned, considering future pandemics.</p>},
  year = {2025},
  journal = {IEEE Computer Graphics and Applications},
  volume = {45},
  pages = {130-138},
  publisher = {IEEE COMPUTER SOC},
  issn = {1558-1756},
  doi = {10.1109/MCG.2024.3509293},
}