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

Chen, M. ORCID: https://orcid.org/0000-0001-5320-5729, Abdul-Rahman, A. ORCID: https://orcid.org/0000-0002-6257-876X, Archambault, D. ORCID: https://orcid.org/0000-0003-4978-8479, Dykes, J. ORCID: https://orcid.org/0000-0002-8096-5763, Ritsos, P. D. ORCID: https://orcid.org/0000-0001-9308-3885, Slingsby, A. ORCID: https://orcid.org/0000-0003-3941-553X, Torsney-Weir, T. ORCID: https://orcid.org/0000-0002-0329-2198, Turkay, C. ORCID: https://orcid.org/0000-0001-6788-251X, Bach, B., Borgo, R. ORCID: https://orcid.org/0000-0003-2875-6793, Brett, A., Fang, H. ORCID: https://orcid.org/0000-0001-9365-7420, Jianu, R. ORCID: https://orcid.org/0000-0002-5834-2658, Khan, S. ORCID: https://orcid.org/0000-0002-6796-5670, Laramee, R. S. ORCID: https://orcid.org/0000-0002-3874-6145, Matthews, L., Nguyen, P. H. ORCID: https://orcid.org/0000-0001-5643-0585, Reeve, R. ORCID: https://orcid.org/0000-0003-2589-8091, Roberts, J. C. ORCID: https://orcid.org/0000-0001-7718-3181, Vidal, F. P. ORCID: https://orcid.org/0000-0002-2768-4524, Wang, Q. ORCID: https://orcid.org/0000-0003-3397-308X, Wood, J. ORCID: https://orcid.org/0000-0001-9270-247X and Xu, Kai ORCID: https://orcid.org/0000-0003-2242-5440 (2022) RAMPVIS: Answering the challenges of building visualisation capabilities for large-scale emergency responses. Epidemics, 39 , 100569. ISSN 1755-4365 [Article] (doi:10.1016/j.epidem.2022.100569)

Preview	PDF - Published version (with publisher's formatting) Available under License Creative Commons Attribution 4.0. Download (3MB) | Preview
	PDF (Journal Pre-Proof PDF file of an article that has undergone enhancements after acceptance) - Other Restricted to Repository staff and depositor only Available under License Creative Commons Attribution-NonCommercial-NoDerivatives 4.0. Download (9MB)

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.

Actions (login required)

View Item

Statistics

DownloadsShow export options

Export as CSVXMLJSON

Activity Overview

6 month trend

31Downloads

6 month trend

51Hits

Additional statistics are available via IRStats2.