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

M. Chen Orcid Logo, A. Abdul-Rahman Orcid Logo, Daniel Archambault Orcid Logo, J. Dykes Orcid Logo, P.D. Ritsos Orcid Logo, A. Slingsby Orcid Logo, Tom Torsney-Weir Orcid Logo, C. Turkay Orcid Logo, B. Bach, Rita Borgo Orcid Logo, A. Brett, H. Fang Orcid Logo, R. Jianu Orcid Logo, S. Khan Orcid Logo, Bob Laramee Orcid Logo, L. Matthews, P.H. Nguyen Orcid Logo, R. Reeve Orcid Logo, J.C. Roberts Orcid Logo, F.P. Vidal Orcid Logo, Q. Wang Orcid Logo, J. Wood Orcid Logo, K. Xu Orcid Logo

Epidemics, Volume: 39, Start page: 100569

Swansea University Authors: Daniel Archambault Orcid Logo, Tom Torsney-Weir Orcid Logo, Rita Borgo Orcid Logo, Bob Laramee Orcid Logo

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Abstract

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...

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Published in: Epidemics
ISSN: 1755-4365
Published: Elsevier BV 2022
Online Access: Check full text

URI: https://cronfa.swan.ac.uk/Record/cronfa59933
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Abstract: 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.
Keywords: Data visualisation; Visual analytics; Pandemic responses; COVID-19; Model development
College: Faculty of Science and Engineering
Start Page: 100569