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

Area of Science:

• Public Health
• Data Science
• Information Visualization

Background:

• The COVID-19 pandemic generated vast datasets across multiple scientific domains.
• Emergency response efforts highlighted an urgent need for effective visualisation and visual analytics (VIS) tools.
• Operational constraints posed significant challenges to developing and deploying VIS capacities.

Purpose of the Study:

• To report the experiences of VIS volunteers supporting COVID-19 response efforts.
• To describe approaches to challenges in requirements analysis, data acquisition, and system development.
• To propose recommendations for a methodology for rapid VIS capacity development in emergencies.

Main Methods:

• A volunteer group within a research consortium provided VIS support for diverse tasks.
• Documenting and reflecting on encountered challenges in VIS development and deployment.
• Analyzing experiences in requirements gathering, data handling, design, and team organization.

Main Results:

• Successful application of VIS to observational, analytical, model-developmental, and disseminative tasks.
• Identification of key challenges in rapid VIS development under operational pressure.
• Formulation of practical approaches to address these challenges.

Conclusions:

• The volunteer experience provides valuable insights into rapid VIS development for emergency response.
• Recommendations are proposed as a foundational step towards a formal methodology.
• Establishing robust VIS capabilities is crucial for effective crisis management and scientific support.