RAMPVIS: Answering the challenges of building visualisation capabilities for large-scale emergency responses.

Autor:	Chen M; University of Oxford, United Kingdom. Electronic address: min.chen@oerc.ox.ac.uk., Abdul-Rahman A; King's College London, United Kingdom., Archambault D; Swansea University, United Kingdom., Dykes J; City, University of London, United Kingdom., Ritsos PD; Bangor University, United Kingdom., Slingsby A; City, University of London, United Kingdom., Torsney-Weir T; Swansea University, United Kingdom., Turkay C; University of Warwick, United Kingdom., Bach B; University of Edinburgh, United Kingdom., Borgo R; King's College London, United Kingdom., Brett A; UK Atomic Energy Authority, United Kingdom., Fang H; Loughborough University, United Kingdom., Jianu R; City, University of London, United Kingdom., Khan S; University of Oxford, United Kingdom; Horus Security Consultancy Ltd., United Kingdom., Laramee RS; University of Nottingham, United Kingdom., Matthews L; University of Glasgow, United Kingdom., Nguyen PH; Red Sift Ltd., United Kingdom., Reeve R; University of Glasgow, United Kingdom., Roberts JC; Bangor University, United Kingdom., Vidal FP; Bangor University, United Kingdom., Wang Q; University of Nottingham, United Kingdom., Wood J; City, University of London, United Kingdom., Xu K; Middlesex University London, United Kingdom.
Jazyk:	angličtina
Zdroj:	Epidemics [Epidemics] 2022 Jun; Vol. 39, pp. 100569. Date of Electronic Publication: 2022 Apr 28.
DOI:	10.1016/j.epidem.2022.100569
Abstrakt:	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. (Copyright © 2022 The Author(s). Published by Elsevier B.V. All rights reserved.)
Databáze:	MEDLINE
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