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

Chen, M. et al. (2022) RAMPVIS: Answering the challenges of building visualisation capabilities for large-scale emergency responses. Epidemics, 39, 100569. (doi: 10.1016/j.epidem.2022.100569) (PMID:35597098) (PMCID:PMC9045880)

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.

• Item Type: Articles
• Additional Information: While this paper reports the RAMPVIS effort during its volunteering period in 2020, the authors appreciate very much the funding from UKRI/EPSRC for the continuation of this effort between February 2021 and January 2022 (EP/V054236/1).
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Reeve, Professor Richard and Matthews, Professor Louise
• Authors: 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., and Xu, K.
• College/School: College of Medical Veterinary and Life Sciences > School of Biodiversity, One Health & Veterinary Medicine
• Journal Name: Epidemics
• Publisher: Elsevier
• ISSN: 1755-4365
• ISSN (Online): 1878-0067
• Published Online: 28 April 2022
• Copyright Holders: Copyright © 2022 The Author(s).
• First Published: First published in Epidemics 39:100569
• Publisher Policy: Reproduced under a Creative Commons Licence