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

Article


Chen, M., Abdul-Rahman, A., Archambault, D., Dykes, J., Ritsos, P., Slingsby, A., Torsney-Weir, T., Turkay, C., Bach, B., Borgo, R., Brett, A., Fang, H., Jianu, R., Khan, S., Laramee, R., Matthews, L., Nguyen, P., Reeve, R., Roberts, J., Vidal, F., Wang, Q., Wood, J. and Xu, K. 2022. RAMPVIS: Answering the challenges of building visualisation capabilities for large-scale emergency responses. Epidemics. 39. https://doi.org/10.1016/j.epidem.2022.100569
TypeArticle
TitleRAMPVIS: Answering the challenges of building visualisation capabilities for large-scale emergency responses
AuthorsChen, M., Abdul-Rahman, A., Archambault, D., Dykes, J., Ritsos, P., Slingsby, A., Torsney-Weir, T., Turkay, C., Bach, B., Borgo, R., Brett, A., Fang, H., Jianu, R., Khan, S., Laramee, R., Matthews, L., Nguyen, P., Reeve, R., Roberts, J., Vidal, F., Wang, Q., Wood, J. and Xu, K.
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.

KeywordsPandemic responses, Data visualisation, Model development, COVID-19, Visual analytics
PublisherElsevier
JournalEpidemics
ISSN1755-4365
Publication dates
Online28 Apr 2022
Print18 May 2022
Publication process dates
Deposited11 May 2022
Accepted19 Apr 2022
Submitted11 Jun 2021
Output statusPublished
Publisher's version
License
File Access Level
Open
Copyright Statement

Published version © 2022 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

Digital Object Identifier (DOI)https://doi.org/10.1016/j.epidem.2022.100569
LanguageEnglish
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