RAMPVIS: Towards a New Methodology for Developing Visualisation Capabilities for Large-scale Emergency Responses
This work addresses the urgent need for rapid visualization capabilities to support large-scale emergency responses, offering recommendations for future development.
This paper reports on the experience of a volunteer group providing visualization support for COVID-19 emergency responses within a large research consortium. They describe their approaches to challenges in requirements analysis, data acquisition, visual design, software design, system development, team organization, and resource planning.
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.