RAMP VIS: Making Visual Analytics an Integral Part of the Technological Infrastructure for Combating COVID-19

  • Funded by UK Research and Innovation (UKRI)
  • Total publications:9 publications

Grant number: EP/V054236/1

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Key facts

  • Disease

    COVID-19
  • Start & end year

    2021
    2021
  • Known Financial Commitments (USD)

    $581,170.95
  • Funder

    UK Research and Innovation (UKRI)
  • Principal Investigator

    Min Chen
  • Research Location

    United Kingdom
  • Lead Research Institution

    University of Oxford
  • Research Priority Alignment

    N/A
  • Research Category

    Epidemiological studies

  • Research Subcategory

    Impact/ effectiveness of control measures

  • Special Interest Tags

    Data Management and Data Sharing

  • Study Type

    Non-Clinical

  • Clinical Trial Details

    N/A

  • Broad Policy Alignment

    Pending

  • Age Group

    Not Applicable

  • Vulnerable Population

    Not applicable

  • Occupations of Interest

    Not applicable

Abstract

Computational modelling of the COVID-19 pandemic has been playing a significant role in the UK's effort to combat COVID-19. Across the country, there are about 100 research teams working on different models, and several dozens have provided simulation, estimation, and prediction to inform the governmental decisions in the four home nations. One noticeable oversight is the under-utilisation of visualization and visual analytics technology in supporting the scientific workflows for model development, which typically consists of a set of iterative processes, such as (a) hypothesis formulation and causality analysis; (b) model development, testing, validation, and comparison; (c) model deployment, monitoring, and improvement; and (d) scientific and public dissemination. Because visualization is widely mistaken only for information or knowledge dissemination, the technology is commonly underused in all other stages of a modelling workflow. Ideally, modelling scientists and epidemiologists could have a quick glance of dynamic data anytime there is a need (cf. stock brokers observing stock market data), access effective overviews of spatiotemporal patterns of the disease development and control (cf., meteorologists observing satellite images, contour maps, etc.), be provided with external memorization of data to stimulate hypotheses and contemplate various decisions (cf. a general pacing around in a war room in front of many maps), and receive advice from an ensemble of analytical algorithms and visualizations about similarity, anomalies, clusters, correlation, causality, and association hidden in the data (cf. a CEO consulting specialists). Ideally, there is a visual analytics infrastructure, as a "standing capacity" (Secretary of State), that can support many modelling teams performing daily observational, analytical, and model-developmental tasks. The proposed VA technical and knowledge infrastructures are essential for combating COVID-19 pandemic, as many epidemiologists are preparing for COVID-10 to be a threat for some time. With the recent introduction of localised control measures, it indicates an additional need for localised VA supports for many local scientists and healthcare professionals. When vaccination starts, there is a need for monitoring and modelling the effectiveness of different vaccines used in different regions. Such a nationwide need can be cost-effectively delivered by the VA technical and knowledge infrastructures.

Publicationslinked via Europe PMC

Last Updated:an hour ago

View all publications at Europe PMC

Preparedness for Visualization in the Next Pandemic.

RAMPVIS: A visualization and visual analytics infrastructure for COVID-19 data.

Dashboard Design Patterns.

FAIR data pipeline: provenance-driven data management for traceable scientific workflows.

Development and Evaluation of Two Approaches of Visual Sensitivity Analysis to Support Epidemiological Modeling.

Visualization for epidemiological modelling: challenges, solutions, reflections and recommendations.

The challenges of data in future pandemics.

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

Propagating Visual Designs to Numerous Plots and Dashboards.