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A data management plan for the NESHIE observational study.

Adéle Strydom1, Jeanne Van Rensburg1, Michael S Pepper1

  • 1Institute for Cellular and Molecular Medicine, Department of Immunology, and SAMRC Extramural Unit for Stem Cell Research and Therapy, Faculty of Health Sciences, University of Pretoria, Pretoria, South Africa.

Frontiers in Genetics
|December 22, 2023
PubMed
Summary
This summary is machine-generated.

A data management plan is crucial for ethical research, especially with vulnerable populations. This study offers a template for managing multi-omics data in low- and middle-income countries (LMICs).

Keywords:
NESHIEdatalegislationmanagementsample

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Area of Science:

  • Data Science
  • Bioinformatics
  • Public Health Research

Background:

  • Effective data management is essential for ethical research, particularly concerning participant data privacy and sample sharing.
  • Existing data management plans often lack specificity for research involving vulnerable populations and complex data types like multi-omics.

Purpose of the Study:

  • To present a comprehensive data management plan template tailored for research involving vulnerable populations in low- and middle-income countries (LMICs).
  • To provide a modifiable outline for managing diverse data, including clinical and multi-omics data from samples, in sensitive research contexts.

Main Methods:

  • Leveraging detailed data management plans from the 'NESHIE study' as a foundation.
  • Developing a template that addresses data governance, participant protection, and the lifecycle of research data and samples.

Main Results:

  • A downloadable, modifiable data management plan template designed for research with vulnerable populations.
  • The template covers the governance, collection, organization, use, storage, preservation, sharing, and access of clinical and multi-omics data.

Conclusions:

  • The developed template offers a robust framework for managing complex research data, particularly in LMICs.
  • This resource aims to facilitate ethical and efficient data handling in clinical research and trials involving vulnerable groups and multi-omics approaches.