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Lookup NU author(s): Dr Daniel ArchambaultORCiD
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
© 2022 The Author(s). The effort for combating the COVID-19 pandemic around the world has resulted in a huge amount of data, e.g., from testing, contact tracing, modelling, treatment, vaccine trials, and more. In addition to numerous challenges in epidemiology, healthcare, biosciences, and social sciences, there has been an urgent need to develop and provide visualisation and visual analytics (VIS) capacities to support emergency responses under difficult operational conditions. In this paper, we report the experience of a group of VIS volunteers who have been working in a large research and development consortium and providing VIS support to various observational, analytical, model-developmental, and disseminative tasks. In particular, we describe our approaches to the challenges that we have encountered in requirements analysis, data acquisition, visual design, software design, system development, team organisation, and resource planning. By reflecting on our experience, we propose a set of recommendations as the first step towards a methodology for developing and providing rapid VIS capacities to support emergency responses.
Author(s): Chen M, Abdul-Rahman A, Archambault D, Dykes J, Ritsos PD, Slingsby A, Torsney-Weir T, Turkay C, Bach B, Borgo R, Brett A, Fang H, Jianu R, Khan S, Laramee RS, Matthews L, Nguyen PH, Reeve R, Roberts JC, Vidal FP, Wang Q, Wood J, Xu K
Publication type: Article
Publication status: Published
Journal: Epidemics
Year: 2022
Volume: 39
Print publication date: 01/06/2022
Online publication date: 28/04/2022
Acceptance date: 19/04/2022
Date deposited: 15/09/2023
ISSN (print): 1755-4365
ISSN (electronic): 1878-0067
Publisher: Elsevier BV
URL: https://doi.org/10.1016/j.epidem.2022.100569
DOI: 10.1016/j.epidem.2022.100569
PubMed id: 35597098
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