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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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DOI (Published version): 10.1016/j.epidem.2022.100569

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
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URI: https://cronfa.swan.ac.uk/Record/cronfa59933
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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. 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spelling 2022-05-27T10:55:23.9556832 v2 59933 2022-05-01 RAMPVIS: Answering the challenges of building visualisation capabilities for large-scale emergency responses 8fa6987716a22304ef04d3c3d50ef266 0000-0003-4978-8479 Daniel Archambault Daniel Archambault true false 6675d91d11195ef4c16eefd3fa316474 0000-0002-0329-2198 Tom Torsney-Weir Tom Torsney-Weir true false c4675d4072e4b2b3921ae57666f1d9ff 0000-0003-2875-6793 Rita Borgo Rita Borgo true false 7737f06e2186278a925f6119c48db8b1 0000-0002-3874-6145 Bob Laramee Bob Laramee true false 2022-05-01 SCS 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. Journal Article Epidemics 39 100569 Elsevier BV 1755-4365 Data visualisation; Visual analytics; Pandemic responses; COVID-19; Model development 1 6 2022 2022-06-01 10.1016/j.epidem.2022.100569 COLLEGE NANME Computer Science COLLEGE CODE SCS Swansea University Other 2022-05-27T10:55:23.9556832 2022-05-01T13:42:04.7018391 Faculty of Science and Engineering School of Mathematics and Computer Science - Computer Science M. Chen 0000-0001-5320-5729 1 A. Abdul-Rahman 0000-0002-6257-876x 2 Daniel Archambault 0000-0003-4978-8479 3 J. Dykes 0000-0002-8096-5763 4 P.D. Ritsos 0000-0001-9308-3885 5 A. Slingsby 0000-0003-3941-553x 6 Tom Torsney-Weir 0000-0002-0329-2198 7 C. Turkay 0000-0001-6788-251x 8 B. Bach 9 Rita Borgo 0000-0003-2875-6793 10 A. Brett 11 H. Fang 0000-0001-9365-7420 12 R. Jianu 0000-0002-5834-2658 13 S. Khan 0000-0002-6796-5670 14 Bob Laramee 0000-0002-3874-6145 15 L. Matthews 16 P.H. Nguyen 0000-0001-5643-0585 17 R. Reeve 0000-0003-2589-8091 18 J.C. Roberts 0000-0001-7718-3181 19 F.P. Vidal 0000-0002-2768-4524 20 Q. Wang 0000-0003-3397-308x 21 J. Wood 0000-0001-9270-247x 22 K. Xu 0000-0003-2242-5440 23 59933__24199__00dee5f9919d47f68b870f9cc18408e5.pdf 59933.pdf 2022-05-27T10:52:09.1135482 Output 3922032 application/pdf Version of Record true © 2022 The Author(s). This is an open access article under the CC BY license true eng http://creativecommons.org/licenses/by/4.0/
title RAMPVIS: Answering the challenges of building visualisation capabilities for large-scale emergency responses
spellingShingle RAMPVIS: Answering the challenges of building visualisation capabilities for large-scale emergency responses
Daniel Archambault
Tom Torsney-Weir
Rita Borgo
Bob Laramee
title_short RAMPVIS: Answering the challenges of building visualisation capabilities for large-scale emergency responses
title_full RAMPVIS: Answering the challenges of building visualisation capabilities for large-scale emergency responses
title_fullStr RAMPVIS: Answering the challenges of building visualisation capabilities for large-scale emergency responses
title_full_unstemmed RAMPVIS: Answering the challenges of building visualisation capabilities for large-scale emergency responses
title_sort RAMPVIS: Answering the challenges of building visualisation capabilities for large-scale emergency responses
author_id_str_mv 8fa6987716a22304ef04d3c3d50ef266
6675d91d11195ef4c16eefd3fa316474
c4675d4072e4b2b3921ae57666f1d9ff
7737f06e2186278a925f6119c48db8b1
author_id_fullname_str_mv 8fa6987716a22304ef04d3c3d50ef266_***_Daniel Archambault
6675d91d11195ef4c16eefd3fa316474_***_Tom Torsney-Weir
c4675d4072e4b2b3921ae57666f1d9ff_***_Rita Borgo
7737f06e2186278a925f6119c48db8b1_***_Bob Laramee
author Daniel Archambault
Tom Torsney-Weir
Rita Borgo
Bob Laramee
author2 M. Chen
A. Abdul-Rahman
Daniel Archambault
J. Dykes
P.D. Ritsos
A. Slingsby
Tom Torsney-Weir
C. Turkay
B. Bach
Rita Borgo
A. Brett
H. Fang
R. Jianu
S. Khan
Bob Laramee
L. Matthews
P.H. Nguyen
R. Reeve
J.C. Roberts
F.P. Vidal
Q. Wang
J. Wood
K. Xu
format Journal article
container_title Epidemics
container_volume 39
container_start_page 100569
publishDate 2022
institution Swansea University
issn 1755-4365
doi_str_mv 10.1016/j.epidem.2022.100569
publisher Elsevier BV
college_str Faculty of Science and Engineering
hierarchytype
hierarchy_top_id facultyofscienceandengineering
hierarchy_top_title Faculty of Science and Engineering
hierarchy_parent_id facultyofscienceandengineering
hierarchy_parent_title Faculty of Science and Engineering
department_str School of Mathematics and Computer Science - Computer Science{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Mathematics and Computer Science - Computer Science
document_store_str 1
active_str 0
description 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.
published_date 2022-06-01T04:17:37Z
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score 11.013148

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