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DataSHIELD: mitigating disclosure risk in a multi-site federated analysis platform.

Demetris Avraam1,2, Rebecca C Wilson2, Noemi Aguirre Chan3

  • 1Department of Public Health, Section of Epidemiology, University of Copenhagen, Copenhagen, DK-1353, Denmark.

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|April 7, 2025
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Summary

DataSHIELD enables federated analysis for large-scale health data, enhancing findings validity. This open-source platform ensures data security and privacy through multi-layered disclosure prevention mechanisms.

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Area of Science:

  • Biomedical Informatics
  • Epidemiology
  • Data Governance

Background:

  • Epidemiologic findings' validity relies on data triangulation and large datasets.
  • Access to health and biomedical data is often restricted by practical, ethico-legal, and governance constraints.
  • Data access requests across jurisdictions are time-consuming due to governance requirements.

Purpose of the Study:

  • To describe the disclosure protection system of DataSHIELD.
  • To present DataSHIELD as a solution for large-scale statistical analysis of health and biomedical data.
  • To highlight DataSHIELD's capabilities in addressing technical and regulatory challenges in data analysis.

Main Methods:

  • DataSHIELD employs federated analysis, enabling remote data analysis without data transfer.
  • The platform is aligned with the 'Five Safes' framework for secure data research access.
  • A multi-layer system of disclosure-preventing mechanisms mitigates disclosure risk during real-time analysis.

Main Results:

  • DataSHIELD provides real-time remote statistical analysis.
  • Disclosure prevention mechanisms are integrated across system, analysis, and governance levels.
  • The software facilitates large-scale statistical analysis of health and biomedical data while adhering to data governance.

Conclusions:

  • DataSHIELD offers a robust solution for secure, federated analysis of sensitive health data.
  • The platform addresses challenges in data access and governance for large-scale research.
  • DataSHIELD enhances the validity of epidemiologic findings through secure data analysis.