RAMPVIS: Answering the Challenges of Building Visualisation Capabilities for Large-scale Emergency Responses
Research output: Contribution to journal › Article › peer-review
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- Chen_et_al_RAMVIS_Epidemics
Accepted author manuscript, 6.75 MB, PDF document
- RAMPVIS
Final published version, 3.74 MB, PDF document
Licence: CC BY Show licence
DOI
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.
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.
Keywords
- Data visualisation, Visual Analytics, Pandemic responses, COVID-19, Model development
Original language | English |
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Article number | 100569 |
Number of pages | 15 |
Journal | Epidemics |
Volume | 39 |
Early online date | 28 Apr 2022 |
DOIs | |
Publication status | Published - Jun 2022 |
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Active Learning Activities in a Collaborative Teacher Setting in Colours, Design and Visualisation
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