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

RAMPVIS: Answering the challenges of building visualisation capabilities for large-scale emergency responses.
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DOI:
10.1016/j.epidem.2022.100569
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发表时间:
2022-06
期刊:
影响因子:
3.8
通讯作者:
Xu, K.
Xu, K.
中科院分区:
医学2区
文献类型:
--
作者:
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.

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全球抗击COVID-19疫情的努力产生了大量数据,例如,从检测、接触者追踪、建模、治疗、疫苗试验等等。除了流行病学、医疗保健、生物科学和社会科学方面的众多挑战外,还迫切需要开发和提供可视化和可视化分析(维斯)能力,以支持在困难的操作条件下的应急响应。在本文中,我们报告了一组维斯志愿者的经验,他们一直在一个大型的研究和开发财团工作,并提供维斯支持各种观测,分析,模型开发和传播任务。特别是,我们描述了我们的方法,我们遇到的挑战,在需求分析,数据采集,视觉设计,软件设计,系统开发,团队组织和资源规划。通过反思我们的经验,我们提出了一套建议,作为制定发展和提供快速维斯能力以支持应急反应的方法的第一步。
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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