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

Lead Research Organisation: University of Oxford
Department Name: Engineering Science

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.

Publications

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Khan S (2022) Propagating Visual Designs to Numerous Plots and Dashboards. in IEEE transactions on visualization and computer graphics

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Khan S (2022) Rapid Development of a Data Visualization Service in an Emergency Response in IEEE Transactions on Services Computing

 
Description (1) We have made a video "Why do we need multiple models?" which is to be distributed widely through social media to inform the public as to the importance of and challenges in epidemiological modelling. (2) We have developed a new technology for create storytelling visualization for individual regions automatically in order to provide the public with data visualization that is relevant to them. (3) We have developed a tool for allowing users around the world who do not have any modelling capability to search for COVID-19 time series similar to their regions, enabling them to observe past data with similar patterns easily and to make informed-decisions about their own regions. (4) We have developed special visualization techniques for aiding the education of school children about COVID-19 modelling in Wales. As these new developments were completed only several weeks ago, we are currently evaluating these technologies and methods while reaching out to potential users.
First Year Of Impact 2022
Sector Communities and Social Services/Policy,Education,Healthcare
Impact Types Societal,Policy & public services

 
Title RAMPVIS Infrastructure 
Description The initial version of this infrastructure was developed by a team of volunteers between June and August 2020 after the team was created in response to the Royal Society's RAMP Call. The infrastructure was hosted at STFC, and it was developed in parallel with that for SCRC's data infrastructure. This infrastructure was made available online by the end of August 2020, and has been alive (at https://vis.scrc.uk/) since. Many new features have been introduced, including several tools developed during the funded period (February 2021 - January 2022). 
Type Of Material Improvements to research infrastructure 
Year Produced 2021 
Provided To Others? Yes  
Impact This R&D effort confirms that it is necessary to provide many epidemiologists and modelling science and their epidemiological modelling workflows with visual analytics support through an appropriate visualization infrastructure. Such an infrastructure should ideally be pre-existed as part of the resilience infrastructure. When such an infrastructure is not available, it is feasible to develop such an infrastructure within a relative short period. 
URL https://vis.scrc.uk/