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Data Management

Resources to help you manage, store, and share your data.

NIH Data Management and Sharing Policy Summary

NIH has issued the Data Management and Sharing (DMS) policy (effective January 25, 2023) to promote the sharing of scientific data. Sharing scientific data accelerates biomedical research discovery, in part, by enabling validation of research results, providing accessibility to high-value datasets, and promoting data reuse for future research studies.

Now, under the DMS policy, NIH intramural investigators will:

  • Prospectively plan for the managing and sharing of scientific data
  • Submit a DMS plan, which is required for scientific data from:
    • Research associated with a ZIA
    • Research associated with a clinical protocol that will undergo IC Initial Scientific Review
    • Research associated with a Genomic Data Sharing project
  • Comply with the approved plan

The plans will address the elements indicated in the Intramural Research Program Data Management and Sharing (IRP DMS) Plan template. The template addresses six NIH-recommended core elements, and allows for the inclusion of IC-specific elements.

DMS Plans for ZIA research projects will be entered into the NIDB. (If available, plans can be submitted through an IC-based electronic system that transfers the information to the NIDB). Plans for research to be conducted on or after January 25, 2023 must be submitted prior to that date. The plans will be reviewed by the Scientific Directors (or their designees), and must be revised if the plan is not approved. In future years, plans can be updated as necessary, and new plans will be added as part of the annual review process. Investigators will submit a description of how they have complied with their approved DMS plan as part of the annual review, starting in 2024.

Even though clinical protocols may be associated with a ZIA, the submission and review process of DMS plans will take into account the current system for review of protocols. Plans supporting a protocol will be entered into the NIDB and exported. The plan will then be submitted as an attachment into the PROTECT system, along with other protocol materials, as part of the IC Initial Scientific Review of protocols. The DMS plan will be reviewed by the IC’s Scientific Review Committee. The IRP DMS template will be used for materials submitted on or after January 25, 2023. For protocols that are ongoing or submitted for IC scientific review prior to January 25, 2023, a plan using the IRP DMS template will be submitted and reviewed as part of the quadrennial scientific review of the protocol.

Types of Data to Share

What Scientific Data Need to Be Shared

Scientific data are defined as the recorded factual material commonly accepted in the scientific community as of sufficient quality to validate and replicate research findings, regardless of whether the data are used to support scholarly publications. Scientific data do not include laboratory notebooks, preliminary analyses, completed case report forms, drafts of scientific papers, plans for future research, peer reviews, communications with colleagues, or physical objects, such as laboratory specimens. See Frequently Asked Questions B1 for additional guidance on what must be shared. Examples of scientific data to be shared are provided here as Appendix 1.

There are justifiable reasons for limiting the sharing of data. These reasons should be described in the DMS plan. See Frequently Asked Questions B4

Data plans for research that is subject to the NIH Genomic Data Sharing policy will now be included as part of the DMS plans. Genomic data sharing considerations, such as where and when genomic data will be shared, will be addressed in the DMS plan.

When Data Need to Be Shared

At a minimum, scientific data supporting a publication must be shared by the time of publication (when the publication first appears, either online or in print). Other scientific data must be shared by the end of the research project or protocol. OIR encourages the sharing of high quality scientific data that are not included in a publication, including “negative results.”

Selecting a Data Repository

  • For some programs and types of data, NIH and/or IC policy may designate specific data repositories to be used.
  • For data generated from research for which no data repository is specified by NIH, researchers are encouraged to select a data repository that is appropriate for the data generated from the research project. Primary consideration should be given to data repositories that are discipline or data-type specific to support effective data discovery and reuse.
  • If no appropriate discipline or data-type specific repository is available, researchers should consider other options, including generalist repositories. For additional information see Selecting a Data Repository and Repositories for Sharing Scientific Data.

Note that submission of a study to ClinicalTrials.gov meets the requirements of FDAAA but does not fulfill the requirements of the Data Management and Sharing Policy.

Data Standards

Plans supporting a clinical protocol will address the use of Common Data Elements (CDE)s, which allow data to be collected in the same way across multiple research studies . The National Library of Medicine (NLM) provides a searchable list of CDEs. All plans will indicate what other standards, if any, will be applied to the scientific data and associated metadata (i.e., data formats, data dictionaries, data identifiers, definitions, unique identifiers, and other data documentation). Many scientific fields have developed and adopted common data standards, while others have not. In such cases, the plan may indicate that no consensus data standards exist for the scientific data and metadata to be generated, preserved, and shared.

 

The following list provides examples of data types to be shared. The list does not include all data types to be considered.

"Omics" Data

  • Genomics and epigenetics (e.g., WGS, WES, EPIC arrays, targeted panels)
  • Transcriptomics e.g., RNA-seq)
  • Microbiomics (e.g., bacteria, virus)
  • Proteomics (e.g., mass spec, RPPA)
  • Metabolomics (e.g., mass spec)

Imaging Data

  • Medical imaging (e.g., ultrasound, MRI, CT)
  • Non-medical imaging (e.g., fluorescence microscopy)
  • Other (e.g., histopathology)

Biological Data

  • Electrophysiology (e.g., sensor data, ECG)
  • Biochemical (e.g., X-ray, NMR, AMF, FRET)
  • Pre-clinical (e.g., PDX growth curve)

Phenotype Data

  • Non-human (e.g. phenotypic features of animal models)
  • Human traits (e.g., blood type)
  • Demographics
  • Clinical data (including specimen information)

Additional Data

  • Clinical trial results
  • Associated metadata
  • Epidemiology/surveillance
  • Administrative
  • Algorithm/Simulation
  • Social/Behavioral
  • Survey/questionnaire

Recommendations

Sample Data Management and Sharing Plans

NIMH provides sample DMS plans on their Data Sharing for Applicants and Awardees page.

Indiana University provides sample DMS plans at https://datasharing.iupui.edu/nih-dms-plan-guidance.html.

Further Guidance