论文标题
RAMPVIS:采用新的方法来开发可视化功能以进行大规模紧急响应
RAMPVIS: Towards a New Methodology for Developing Visualisation Capabilities for Large-scale Emergency Responses
论文作者
论文摘要
与世界各地的Covid-19大流行作斗争的努力导致了大量数据,例如测试,接触跟踪,建模,治疗,疫苗试验等。除了流行病学,医疗保健,生物科学和社会科学方面的许多挑战外,迫切需要开发和提供可视化和视觉分析(VIS)能力(VIS),以支持在困难的操作条件下的紧急响应。在本文中,我们报告了一群志愿者的经验,他们一直在大型的研发联盟工作,并为各种观察,分析,模型发展和传播任务提供支持。特别是,我们描述了我们在需求分析,数据采集,视觉设计,软件设计,系统开发,团队组织和资源计划中遇到的挑战的方法。通过反思我们的经验,我们提出了一组建议,作为迈向发展和提供快速的VIS能力以支持紧急响应的方法的第一步。
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.