Data Management Section
NIH describes research data management as practices that can include validating, organizing, protecting, maintaining, and processing scientific data, giving this section a process-and-stewardship focus rather than an inferential-analysis focus. NIH guidance is U.S. funding guidance and not a universal manuscript template. Keep data management distinct from a Data Analysis section, which explains analytical methods, and from a Data Availability statement, which addresses access or sharing.
A Data Management section explains how study data were organized, validated, protected, maintained, processed, or otherwise managed during the research workflow.
Key details
Important caveats
Scope Boundary
NIH guidance is U.S. funding guidance and not a universal manuscript template. Keep data management distinct from a Data Analysis section, which explains analytical methods, and from a Data Availability statement, which addresses access or sharing.
Further guidance
Content
Describe the management practices that materially affect data integrity, security, organization, quality, or reproducibility, using the level of detail appropriate to the study and venue.
Purpose
A Data Management section explains how study data were organized, validated, protected, maintained, processed, or otherwise managed during the research workflow.
Sources and evidence
Sources are shown with the role they play in this guide. Historical or style-sensitive claims are kept within the evidence boundary described above.
- Data Management — NIH (opens in a new tab)National Institutes of Health · Current U.S. NIH guidance defining research data management activities including validation, organization, protection, maintenance, and processing.