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DataSHIELD: an ethically robust solution to multiple-site individual-level data analysis.

Isabelle Budin-Ljøsne1, Paul Burton, Julia Isaeva

  • 1Division of Epidemiology, Department of Genes and Environment, Norwegian Institute of Public Health, Oslo, Norway.

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DataSHIELD (Data Aggregation Through Anonymous Summary-statistics from Harmonised Individual levEL Databases) offers a robust solution for data sharing concerns. It protects participant privacy and rights, addressing ethical issues in multi-study data analysis.

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Area of Science:

  • Bioinformatics
  • Data Privacy
  • Research Ethics

Background:

  • DataSHIELD enables co-analysis of individual-level data without physical sharing.
  • Previous work confirmed DataSHIELD's compliance with UK confidentiality laws.
  • This study examines DataSHIELD's broader ethical data-sharing considerations.

Purpose of the Study:

  • To investigate DataSHIELD's capacity to address ethics-related data-sharing concerns.
  • To evaluate mechanisms for protecting participant rights and data privacy in distributed research.

Main Methods:

  • Literature search to identify ethics-related data-sharing concerns.
  • Multidisciplinary workshop to systematically examine these concerns.
  • Assessment of DataSHIELD's proposed mechanisms against identified ethical issues.

Main Results:

  • DataSHIELD addresses privacy, confidentiality, and participant rights during and after data sharing.
  • Data remains under the direct management of the originating study.
  • Supervised data processing and querying in a protected environment mitigate risks.
  • Eliminates issues with returning individual research results, retaining responsibility at the study of origin.

Conclusions:

  • DataSHIELD presents an innovative and effective solution for common ethics-related data-sharing challenges.
  • It facilitates secure and ethical collaborative research across multiple studies.