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

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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Autores principales: Chen, M., Abdul-Rahman, A., Archambault, D., Dykes, J., Ritsos, P.D., Slingsby, A., Torsney-Weir, T., Turkay, C., Bach, B., Borgo, R., Brett, A., Fang, H., Jianu, R., Khan, S., Laramee, R.S., Matthews, L., Nguyen, P.H., Reeve, R., Roberts, J.C., Vidal, F.P., Wang, Q., Wood, J., Xu, K.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Author(s). Published by Elsevier B.V. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9045880/
https://www.ncbi.nlm.nih.gov/pubmed/35597098
http://dx.doi.org/10.1016/j.epidem.2022.100569
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author Chen, M.
Abdul-Rahman, A.
Archambault, D.
Dykes, J.
Ritsos, P.D.
Slingsby, A.
Torsney-Weir, T.
Turkay, C.
Bach, B.
Borgo, R.
Brett, A.
Fang, H.
Jianu, R.
Khan, S.
Laramee, R.S.
Matthews, L.
Nguyen, P.H.
Reeve, R.
Roberts, J.C.
Vidal, F.P.
Wang, Q.
Wood, J.
Xu, K.
author_facet Chen, M.
Abdul-Rahman, A.
Archambault, D.
Dykes, J.
Ritsos, P.D.
Slingsby, A.
Torsney-Weir, T.
Turkay, C.
Bach, B.
Borgo, R.
Brett, A.
Fang, H.
Jianu, R.
Khan, S.
Laramee, R.S.
Matthews, L.
Nguyen, P.H.
Reeve, R.
Roberts, J.C.
Vidal, F.P.
Wang, Q.
Wood, J.
Xu, K.
author_sort Chen, M.
collection PubMed
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.
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spelling pubmed-90458802022-04-28 RAMPVIS: Answering the challenges of building visualisation capabilities for large-scale emergency responses Chen, M. Abdul-Rahman, A. Archambault, D. Dykes, J. Ritsos, P.D. Slingsby, A. Torsney-Weir, T. Turkay, C. Bach, B. Borgo, R. Brett, A. Fang, H. Jianu, R. Khan, S. Laramee, R.S. Matthews, L. Nguyen, P.H. Reeve, R. Roberts, J.C. Vidal, F.P. Wang, Q. Wood, J. Xu, K. Epidemics Article 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. The Author(s). Published by Elsevier B.V. 2022-06 2022-04-28 /pmc/articles/PMC9045880/ /pubmed/35597098 http://dx.doi.org/10.1016/j.epidem.2022.100569 Text en © 2022 The Author(s) Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.
spellingShingle Article
Chen, M.
Abdul-Rahman, A.
Archambault, D.
Dykes, J.
Ritsos, P.D.
Slingsby, A.
Torsney-Weir, T.
Turkay, C.
Bach, B.
Borgo, R.
Brett, A.
Fang, H.
Jianu, R.
Khan, S.
Laramee, R.S.
Matthews, L.
Nguyen, P.H.
Reeve, R.
Roberts, J.C.
Vidal, F.P.
Wang, Q.
Wood, J.
Xu, K.
RAMPVIS: Answering the challenges of building visualisation capabilities for large-scale emergency responses
title 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_short 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
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9045880/
https://www.ncbi.nlm.nih.gov/pubmed/35597098
http://dx.doi.org/10.1016/j.epidem.2022.100569
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