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

被引：9

作者：

Chen, M. ^{[1
]}

Abdul-Rahman, A. ^{[2
]}

Archambault, D. ^{[3
]}

Dykes, J. ^{[4
]}

Ritsos, P. D. ^{[5
]}

Slingsby, A. ^{[4
]}

Torsney-Weir, T. ^{[3
]}

Turkay, C. ^{[6
]}

Bach, B. ^{[7
]}

Borgo, R. ^{[2
]}

Brett, A. ^{[8
]}

Fang, H. ^{[9
]}

Jianu, R. ^{[4
]}

Khan, S. ^{[1
,10
]}

Laramee, R. S. ^{[11
]}

Matthews, L. ^{[12
]}

Nguyen, P. H. ^{[13
]}

Reeve, R. ^{[12
]}

Roberts, J. C. ^{[5
]}

Vidal, F. P. ^{[5
]}

Wang, Q. ^{[11
]}

Wood, J. ^{[4
]}

Xu, K. ^{[14
]}

机构：

[1] Univ Oxford, Oxford, England

[2] Kings Coll London, London, England

[3] Swansea Univ, Swansea, Wales

[4] Univ London, London, England

[5] Bangor Univ, Bangor, Wales

[6] Univ Warwick, Coventry, W Midlands, England

[7] Univ Edinburgh, Edinburgh, Scotland

[8] UK Atom Energy Author, Oxford, England

[9] Loughborough Univ, Loughborough, England

[10] Horus Secur Consultancy Ltd, Oxford, England

[11] Univ Nottingham, Nottingham, England

[12] Univ Glasgow, Glasgow, Scotland

[13] Red Sift Ltd, London, England

[14] Middlesex Univ London, London, England

来源：

EPIDEMICS | 2022年 / 39卷

基金：

英国工程与自然科学研究理事会;

关键词：

Data visualisation; Visual analytics; Pandemic responses; COVID-19; Model development; DECISION-SUPPORT; VISUAL ANALYTICS; DESIGN; UNCERTAINTY; FLOW; DASHBOARDS; TOOL;

D O I：

10.1016/j.epidem.2022.100569

中图分类号：

R51 [传染病];

学科分类号：

100401 ;

摘要：

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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