Visualization for Epidemiological Modelling: Challenges, Solutions, Reflections & Recommendations

Jason Dykes; Alfie Abdul-Rahman; Daniel Archambault; Benjamin Bach; Rita Borgo; Min Chen; Jessica Enright; Hui Fang; Elif E. Firat; Euan Freeman; Tuna Gönen; Claire Harris; Radu Jianu; Nigel W. John; Saiful Khan; Andrew Lahiff; Robert S. Laramee; Louise Matthews; Sibylle Mohr; Phong H. Nguyen; Alma A. M. Rahat; Richard Reeve; Panagiotis D. Ritsos; Jonathan C. Roberts; Aidan Slingsby; Ben Swallow; Thomas Torsney-Weir; Cagatay Turkay; Robert Turner; Franck Vidal; Qiru Wang; Jo Wood; Kai Xu

doi:10.1098/rsta.2021.0299

Visualization for Epidemiological Modelling: Challenges, Solutions, Reflections & Recommendations

Jason Dykes
, Alfie Abdul-Rahman
, Daniel Archambault
, Benjamin Bach
, Rita Borgo
, Min Chen
, Jessica Enright
, Hui Fang
, Elif E. Firat
, Euan Freeman
, Tuna Gönen
, Claire Harris
, Radu Jianu
, Nigel W. John
, Saiful Khan
, Andrew Lahiff
, Robert S. Laramee
, Louise Matthews
, Sibylle Mohr
, Phong H. Nguyen

Alma A. M. Rahat, Richard Reeve, Panagiotis D. Ritsos, Jonathan C. Roberts, Aidan Slingsby, Ben Swallow, Thomas Torsney-Weir, Cagatay Turkay, Robert Turner, Franck Vidal, Qiru Wang, Jo Wood, Kai Xu

School of Computer Science & Engineering

City University of London
Swansea University
King's College London
University of Oxford
University of Glasgow
Loughborough University
University of Nottingham
Biomathematics and Statistics Scotland
UK Atomic Energy Authority
University of Warwick
University of Sheffield
Middlesex University
University of Edinburgh
University of Chester

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

90 Downloads (Pure)

Abstract

We report on an ongoing collaboration between epidemiological modellers and visualization researchers by documenting and reflecting upon knowledge constructs – a series of ideas, approaches and methods taken from existing visualization research and practice – deployed and developed to support modelling of the COVID-19 pandemic. Structured independent commentary on these efforts is synthesized through iterative reflection to develop: evidence of the effectiveness and value of visualization in this context; open problems upon which the research communities may focus; guidance for future activity of this type; and recommendations to safeguard the achievements and promote, advance, secure and prepare for future collaborations of this kind. In describing and comparing a series of related projects that were undertaken in unprecedented conditions, our hope is that this unique report, and its rich interactive supplementary materials, will guide the scientific community in embracing visualization in its observation, analysis and modelling of data as well as in disseminating findings. Equally we hope to encourage the visualization community to engage with impactful science in addressing its emerging data challenges. If we are successful, this showcase of activity may stimulate mutually beneficial engagement between communities with complementary expertise to address problems of significance in epidemiology and beyond. https://ramp-vis.github.io/RAMPVIS-PhilTransA-Supplement/

Original language	English
Article number	20210299
Number of pages	33
Journal	Philosophical Transactions of the Royal Society A
Volume	380
Issue number	2233
Early online date	15 Aug 2022
DOIs	https://doi.org/10.1098/rsta.2021.0299
Publication status	Published - 3 Oct 2022

Keywords

visualization
epidemiological modelling
visual design
computational notebooks
Visual analytics

Access to Document

10.1098/rsta.2021.0299Licence: CC BY

rsta.2021.0299Final published version, 1.16 MBLicence: CC BY

https://arxiv.org/pdf/2204.06946.pdfLicence: CC BY

RAMP VIS: Making Visual Analytics an Integral Part of the Technological Infrastructure for Combating COVID-19
Vidal, F. (PI)
1/02/21 → 1/08/22
Project: Research

Challenges and Opportunities in Data Visualization Education: A Call to Action
Bach, B., Keck, M., Rajabiyazdi, F., Losev, T., Meirelles, I., Dykes, J., Laramee, R. S., AlKadi, M., Stoiber, C., Huron, S., Perin, C., Morais, L., Aigner, W., Kosminsky, D., Boucher, M., Knudsen, S., Manataki, A., Aerts, J., Hinrichs, U. & Roberts, J. C. & 1 others, Carpendale, S., Jan 2024, In: IEEE Transactions on visualization and computer graphics. 30, p. 649-660 12 p.
Research output: Contribution to journal › Article › peer-review

Open Access
File
105 Downloads (Pure)
Active Learning Activities in a Collaborative Teacher Setting in Colours, Design and Visualisation
Roberts, J. C., 29 Apr 2022, In: Computers. 11, 5, 21 p., 68.
Research output: Contribution to journal › Article › peer-review

Open Access

EduVis : Workshop on Visualization Education, Literacy, and Activities
Keck, M. (Chair), Huron, S. (Chair), Panagiotidou, G. (Chair), Stoiber, C. (Chair), Rajabiyazdi, F. (Chair), Perin, C. (Chair), Roberts, J. (Chair) & Bach, B. (Chair)
22 Oct 2023 → 27 Oct 2023
Activity: Participating in or organising an event › Participation in Academic conference

Cite this

Dykes, J., Abdul-Rahman, A., Archambault, D., Bach, B., Borgo, R., Chen, M., Enright, J., Fang, H., Firat, E. E., Freeman, E., Gönen, T., Harris, C., Jianu, R., John, N. W., Khan, S., Lahiff, A., Laramee, R. S., Matthews, L., Mohr, S., ... Xu, K. (2022). Visualization for Epidemiological Modelling: Challenges, Solutions, Reflections & Recommendations. Philosophical Transactions of the Royal Society A, 380(2233), Article 20210299. https://doi.org/10.1098/rsta.2021.0299

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title = "Visualization for Epidemiological Modelling: Challenges, Solutions, Reflections \& Recommendations",

abstract = "We report on an ongoing collaboration between epidemiological modellers and visualization researchers by documenting and reflecting upon knowledge constructs – a series of ideas, approaches and methods taken from existing visualization research and practice – deployed and developed to support modelling of the COVID-19 pandemic. Structured independent commentary on these efforts is synthesized through iterative reflection to develop: evidence of the effectiveness and value of visualization in this context; open problems upon which the research communities may focus; guidance for future activity of this type; and recommendations to safeguard the achievements and promote, advance, secure and prepare for future collaborations of this kind. In describing and comparing a series of related projects that were undertaken in unprecedented conditions, our hope is that this unique report, and its rich interactive supplementary materials, will guide the scientific community in embracing visualization in its observation, analysis and modelling of data as well as in disseminating findings. Equally we hope to encourage the visualization community to engage with impactful science in addressing its emerging data challenges. If we are successful, this showcase of activity may stimulate mutually beneficial engagement between communities with complementary expertise to address problems of significance in epidemiology and beyond. https://ramp-vis.github.io/RAMPVIS-PhilTransA-Supplement/",

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Dykes, J, Abdul-Rahman, A, Archambault, D, Bach, B, Borgo, R, Chen, M, Enright, J, Fang, H, Firat, EE, Freeman, E, Gönen, T, Harris, C, Jianu, R, John, NW, Khan, S, Lahiff, A, Laramee, RS, Matthews, L, Mohr, S, Nguyen, PH, Rahat, AAM, Reeve, R, Ritsos, PD , Roberts, JC, Slingsby, A, Swallow, B, Torsney-Weir, T, Turkay, C, Turner, R, Vidal, F, Wang, Q, Wood, J & Xu, K 2022, 'Visualization for Epidemiological Modelling: Challenges, Solutions, Reflections & Recommendations', Philosophical Transactions of the Royal Society A, vol. 380, no. 2233, 20210299. https://doi.org/10.1098/rsta.2021.0299

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AU - Dykes, Jason

AU - Abdul-Rahman, Alfie

AU - Archambault, Daniel

AU - Bach, Benjamin

AU - Borgo, Rita

AU - Chen, Min

AU - Enright, Jessica

AU - Fang, Hui

AU - Firat, Elif E.

AU - Freeman, Euan

AU - Gönen, Tuna

AU - Harris, Claire

AU - Jianu, Radu

AU - John, Nigel W.

AU - Khan, Saiful

AU - Lahiff, Andrew

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AU - Matthews, Louise

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AU - Nguyen, Phong H.

AU - Rahat, Alma A. M.

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KW - visualization

KW - epidemiological modelling

KW - visual design

KW - computational notebooks

KW - Visual analytics

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DO - 10.1098/rsta.2021.0299

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JF - Philosophical Transactions of the Royal Society A

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ER -

Visualization for Epidemiological Modelling: Challenges, Solutions, Reflections & Recommendations

Abstract

Keywords

Access to Document

Fingerprint

Projects

RAMP VIS: Making Visual Analytics an Integral Part of the Technological Infrastructure for Combating COVID-19

Research output

Challenges and Opportunities in Data Visualization Education: A Call to Action

Active Learning Activities in a Collaborative Teacher Setting in Colours, Design and Visualisation

Activities

EduVis : Workshop on Visualization Education, Literacy, and Activities

Cite this