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  1. Home
  2. Research Domains
  3. Information And Computing Sciences
  4. Data Management And Data Science
  5. Query Processing And Optimisation
  6. The Pandemic Response Commons

The Pandemic Response Commons

Matthew Trunnell1, Casey Frankenberger2, Bala Hota2

  • 1Open Commons Consortium, Chicago, IL 60607, United States.

JAMIA Open
|April 15, 2024

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View abstract on PubMed

Summary
This summary is machine-generated.

The Pandemic Response Commons (PRC) is a new data platform for epidemic research, built on open-source technology. It facilitates data sharing and analysis for researchers studying pandemics.

Area of Science:

  • Epidemiology
  • Data Science
  • Public Health Informatics

Background:

  • Data commons are essential platforms for managing and sharing research data within a community.
  • The Pandemic Response Commons (PRC) was specifically designed to support researchers during epidemics and pandemics.

Purpose of the Study:

  • To develop and implement a robust data commons for pandemic research.
  • To establish a scalable and secure platform for managing diverse epidemiological datasets.

Main Methods:

  • The PRC utilizes the open-source Gen3 data platform.
  • A consortium of regional organizations was formed to develop and operate the PRC.
  • Data governance followed NIST SP 800-53 standards, with a consensus data model for harmonization.
Keywords:
data commonsdata sharingdata systemspandemic

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Main Results:

  • A general PRC and a regional instance, the Chicagoland COVID-19 Commons, were established.
  • Curated datasets include COVID-19 case statistics, clinical data, and viral variant information.
  • The platform was configured for moderate security controls.

Conclusions:

  • A PRC should be operational before an epidemic to ensure rapid response.
  • Regional PRC instances can integrate into larger data ecosystems or data meshes for enhanced pandemic preparedness.
  • The PRC provides a valuable infrastructure for collaborative pandemic research and data sharing.
regional data commons