Panagiotis D. Ritsos

MEng PhD Essex, FHEA

Senior Lecturer in Visualization

XReality, Visualization and
Analytics (XRVA) Lab
Visualization, Data, Modelling and
Graphics (VDMG) research group,
School of Computer Science
and Electronic Engineering,
Bangor University,
Dean Street, Bangor,
Gwynedd, UK, LL57 1UT

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RAMPVIS: Answering the Challenges of Building Visualisation Capabilities for Large-scale Emergency Responses

Teaser for RAMPVIS: Answering the Challenges of Building Visualisation Capabilities for Large-scale Emergency Responses

Abstract

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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Citation

M. Chen, A. Abdul-Rahman, D. Archambault, J. Dykes, A. Slingsby, P. D. Ritsos, T. Torsney-Weir, C. Turkay, B. Bach, R. Borgo, A. Brett, H. Fang, R. Jianu, S. Khan, R. S. Laramee, P. H. Nguyen, R. Reeve, J. C. Robert, F. Vidal, Q. Wang, J. Wood, and K. Xu, “RAMPVIS: Answering the Challenges of Building Visualisation Capabilities for Large-scale Emergency Responses,” Epidemics, vol. 39, no. 100569, Jun. 2022.  doi:10.1016/j.epidem.2022.100569

Bibtex

@article{Chen-et-al-Epidemics-2022,
  author = {Chen, Min and Abdul-Rahman, Alfie and Archambault, Daniel and Dykes, Jason and Slingsby, Aidan and Ritsos, Panagiotis D. and Torsney-Weir, Thomas and Turkay, Cagatay and Bach, Benjamin and Borgo, Rita and Brett, Alys and Fang, Hui and Jianu, Radu and Khan, Shaiful and Laramee, Robert S. and Nguyen, Phong H. and Reeve, Richard and Robert, Jonathan C. and Vidal, Franck and Wang, Qiru and Wood, Jo and Xu, Kai},
  title = {RAMPVIS: Answering the Challenges of Building Visualisation Capabilities for Large-scale Emergency Responses},
  journal = {Epidemics},
  year = {2022},
  volume = {39},
  month = jun,
  number = {100569},
  doi = {10.1016/j.epidem.2022.100569}
}