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

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Visualization for Epidemiological Modelling: Challenges, Solutions, Reflections & Recommendations. / Dykes, Jason; Abdul-Rahman, Alfie; Archambault, Daniel et al.
In: Philosophical Transactions of the Royal Society A, Vol. 380, No. 2233, 20210299, 03.10.2022.

Research output: Contribution to journalArticlepeer-review

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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

APA

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

CBE

Dykes J, Abdul-Rahman A, Archambault D, Bach B, Borgo R, Chen M, Enright J, Fang H, Firat EE, Freeman E, et al. 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

MLA

VancouverVancouver

Dykes J, Abdul-Rahman A, Archambault D, Bach B, Borgo R, Chen M et al. Visualization for Epidemiological Modelling: Challenges, Solutions, Reflections & Recommendations. Philosophical Transactions of the Royal Society A. 2022 Oct 3;380(2233):20210299. Epub 2022 Aug 15. doi: https://doi.org/10.1098/rsta.2021.0299

Author

Dykes, Jason ; Abdul-Rahman, Alfie ; Archambault, Daniel et al. / Visualization for Epidemiological Modelling: Challenges, Solutions, Reflections & Recommendations. In: Philosophical Transactions of the Royal Society A. 2022 ; Vol. 380, No. 2233.

RIS

TY - JOUR

T1 - Visualization for Epidemiological Modelling: Challenges, Solutions, Reflections & Recommendations

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

AU - Laramee, Robert S.

AU - Matthews, Louise

AU - Mohr, Sibylle

AU - Nguyen, Phong H.

AU - Rahat, Alma A. M.

AU - Reeve, Richard

AU - Ritsos, Panagiotis D.

AU - Roberts, Jonathan C.

AU - Slingsby, Aidan

AU - Swallow, Ben

AU - Torsney-Weir, Thomas

AU - Turkay, Cagatay

AU - Turner, Robert

AU - Vidal, Franck

AU - Wang, Qiru

AU - Wood, Jo

AU - Xu, Kai

PY - 2022/10/3

Y1 - 2022/10/3

N2 - 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/

AB - 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/

KW - visualization

KW - epidemiological modelling

KW - visual design

KW - computational notebooks

KW - Visual analytics

U2 - https://doi.org/10.1098/rsta.2021.0299

DO - https://doi.org/10.1098/rsta.2021.0299

M3 - Article

VL - 380

JO - Philosophical Transactions of the Royal Society A

JF - Philosophical Transactions of the Royal Society A

SN - 1364-503X

IS - 2233

M1 - 20210299

ER -