Empowering Communities: Tailored Pandemic Data Visualization for Varied Tasks and Users Article Swipe
Tom Baumgartl
,
Mohammad Ghoniem
,
Tatiana von Landesberger
,
G. Elisabeta Marai
,
Silvia Miksch
,
Sibylle Mohr
,
Simone Scheithauer
,
N. N. Srivastava
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1109/mcg.2024.3509293
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1109/mcg.2024.3509293
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.
Related Topics
Concepts
Computer science
Visualization
Data visualization
Pandemic
Human–computer interaction
Data science
World Wide Web
Coronavirus disease 2019 (COVID-19)
Artificial intelligence
Disease
Pathology
Medicine
Infectious disease (medical specialty)
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1109/mcg.2024.3509293
- OA Status
- hybrid
- References
- 9
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4409427353
All OpenAlex metadata
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https://openalex.org/W4409427353Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1109/mcg.2024.3509293Digital Object Identifier
- Title
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Empowering Communities: Tailored Pandemic Data Visualization for Varied Tasks and UsersWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2025Year of publication
- Publication date
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2025-01-01Full publication date if available
- Authors
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Tom Baumgartl, Mohammad Ghoniem, Tatiana von Landesberger, G. Elisabeta Marai, Silvia Miksch, Sibylle Mohr, Simone Scheithauer, N. N. SrivastavaList of authors in order
- Landing page
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https://doi.org/10.1109/mcg.2024.3509293Publisher landing page
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YesWhether a free full text is available
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hybridOpen access status per OpenAlex
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https://doi.org/10.1109/mcg.2024.3509293Direct OA link when available
- Concepts
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Computer science, Visualization, Data visualization, Pandemic, Human–computer interaction, Data science, World Wide Web, Coronavirus disease 2019 (COVID-19), Artificial intelligence, Disease, Pathology, Medicine, Infectious disease (medical specialty)Top concepts (fields/topics) attached by OpenAlex
- Cited by
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0Total citation count in OpenAlex
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9Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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