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COVID-19 data visualization public welfare activity.

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  • 1Alicloud, China.

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This summary is machine-generated.

This study highlights a data visualization initiative launched during the COVID-19 pandemic. It aimed to develop tools for public understanding and frontline support in combating the epidemic.

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Area of Science:

  • Data Science
  • Public Health
  • Computer Graphics

Background:

  • The COVID-19 pandemic emerged in early 2020, necessitating rapid responses.
  • A collaborative public welfare activity focused on epidemic data visualization was initiated.
  • Key organizations involved included CCF CAD & CG Technical Committee, Alibaba Cloud Tianchi, JiqiZhixin, Alibaba Cloud DataV, and DataWhale.

Purpose of the Study:

  • To engage developers in creating data visualization solutions for the COVID-19 pandemic.
  • To address demand scenarios including epidemic display, popular science, trend prediction, and resource management.
  • To foster the discovery of relationships within complex, multi-source data for public benefit.

Main Methods:

  • Developers were tasked with creating data visualization entries.
  • Entries were categorized into popular science publicity and application scenarios.
  • Focus was placed on discovering insights from heterogeneous, multi-source data.

Main Results:

  • The initiative generated diverse data visualization works.
  • Popular science category focused on public-facing information about the epidemic.
  • Application scenario category provided tools for frontline workers and institutions.

Conclusions:

  • Data visualization proved effective in communicating complex epidemic information.
  • The project supported public understanding and frontline anti-epidemic efforts.
  • Collaborative data visualization initiatives can aid in public health crises.