Empowering Communities: Tailored Pandemic Data Visualization for Varied Tasks and Users

Tom Baumgartl; Mohammad Ghoniem; Tatiana Von Landesberger; G. Elisabeta Marai; Silvia Miksch; Sibylle Mohr; Simone Scheithauer; Nikita Srivastava; Melanie Tory; Daniel Keefe

doi:10.1109/MCG.2024.3509293

Empowering Communities: Tailored Pandemic Data Visualization for Varied Tasks and Users

Tom Baumgartl
, Mohammad Ghoniem
, Tatiana Von Landesberger
, G. Elisabeta Marai
, Silvia Miksch
, Sibylle Mohr
, Simone Scheithauer
, Nikita Srivastava
, Melanie Tory
, Daniel Keefe

Computer Science and Engineering

Research output: Contribution to journal › Article › peer-review

1 Scopus citations

Abstract

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.

Original language	English (US)
Pages (from-to)	130-138
Number of pages	9
Journal	IEEE Computer Graphics and Applications
Volume	45
Issue number	1
DOIs	https://doi.org/10.1109/MCG.2024.3509293
State	Published - 2025

Bibliographical note

Publisher Copyright:
© 1981-2012 IEEE.

PubMed: MeSH publication types

Journal Article
Research Support, U.S. Gov't, Non-P.H.S.
Research Support, Non-U.S. Gov't
Research Support, N.I.H., Extramural

Publisher link

10.1109/MCG.2024.3509293

Find It

Find It at U of M Libraries

Cite this

@article{c6a12bab82b74b7e9318917a5e540d9d,

title = "Empowering Communities: Tailored Pandemic Data Visualization for Varied Tasks and Users",

abstract = "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.",

author = "Tom Baumgartl and Mohammad Ghoniem and \{Von Landesberger\}, Tatiana and Marai, \{G. Elisabeta\} and Silvia Miksch and Sibylle Mohr and Simone Scheithauer and Nikita Srivastava and Melanie Tory and Daniel Keefe",

note = "Publisher Copyright: {\textcopyright} 1981-2012 IEEE.",

year = "2025",

doi = "10.1109/MCG.2024.3509293",

language = "English (US)",

volume = "45",

pages = "130--138",

journal = "IEEE Computer Graphics and Applications",

issn = "0272-1716",

publisher = "IEEE Computer Society",

number = "1",

}

TY - JOUR

T1 - Empowering Communities

T2 - Tailored Pandemic Data Visualization for Varied Tasks and Users

AU - Baumgartl, Tom

AU - Ghoniem, Mohammad

AU - Von Landesberger, Tatiana

AU - Marai, G. Elisabeta

AU - Miksch, Silvia

AU - Mohr, Sibylle

AU - Scheithauer, Simone

AU - Srivastava, Nikita

AU - Tory, Melanie

AU - Keefe, Daniel

PY - 2025

Y1 - 2025

N2 - 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.

AB - 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.

UR - https://www.scopus.com/pages/publications/105003146840

UR - https://www.scopus.com/pages/publications/105003146840#tab=citedBy

U2 - 10.1109/MCG.2024.3509293

DO - 10.1109/MCG.2024.3509293

M3 - Article

C2 - 40227911

AN - SCOPUS:105003146840

SN - 0272-1716

VL - 45

SP - 130

EP - 138

JO - IEEE Computer Graphics and Applications

JF - IEEE Computer Graphics and Applications

IS - 1

ER -

Empowering Communities: Tailored Pandemic Data Visualization for Varied Tasks and Users

Abstract

Bibliographical note

PubMed: MeSH publication types

Publisher link

Find It

Other files and links

Fingerprint

Cite this