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Plan the data handoff before the project ends

Describe what another person will receive, how they will interpret it, who can access it and who is responsible for keeping it usable.

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Data handoff planner

Give every research output an owner, a home and a release date

List what the project produces. For each output, record who owns it, where it lives now, who may access it and where it goes at the end. The planner flags gaps and drafts the two written parts of an NIH Data Management and Sharing Plan from the same list.

Worked example, fictional. A fictional non-human imaging study with three outputs. Human-participant data would need its own consent, privacy and access assessment.

The project

Outputs

Data, code, images, protocols: anything someone would need to check or reuse the work.

Raw microscope images

Segmentation code

Instrument calibration logs

Your data handoff plan

3 outputsNo gaps

OutputOwnerAccessGoes to
Raw microscope imagesImaging leadOpenBioImage Archive, At publication
Segmentation codePostdocOpenGitHub release archived to Zenodo, At publication
Instrument calibration logsLab managerRestrictedAvailable on request, After the study ends

NIH 2026 DMS Plan drafts

Elements 1 to 3 and 5 are yes or no answers on NIH's form. These drafts cover the two written elements.

Element 6, data types and repository 29 of 100 words
Raw microscope images (raw data, OME-TIFF): BioImage Archive. Segmentation code (code or software, Python): GitHub release archived to Zenodo. Instrument calibration logs (protocols and documentation, CSV): Available on request.

Element 4, limitations 14 of 300 words
Instrument calibration logs will have restricted access because they contain the vendor's proprietary configuration.

Use and limits

Operational preparation, not a funder-compliant application form or legal advice. NIH requires its 2026 DMS Plan format. Use the current official form and your institution's approvals for submissions.

Nothing you type leaves this page or is saved. Printable worksheet (PDF, 2 pages)

Go deeper

Step 1

Start with a concrete research output

Work backward from a figure, table or reusable dataset. These are Manusights planning questions; the applicable award, consent, institutional and journal requirements still control.

Name the package
List the relevant data version, analysis code, software environment and documentation. Separate raw, cleaned and derived files so a recipient can identify the input behind an output.
Write the README now
Explain variables, units, missing-value codes, processing steps, file relationships and responsible contacts. State which steps cannot be reproduced and why.

Step 2

Decide access before promising openness

FAIR's accessibility principles allow authentication and authorization where needed. FAIR does not mean every file must be publicly downloadable.

Assign the decision
Have the responsible institutional owner review consent, agreements and disclosure risks. Specify open, controlled or unavailable access for each part of the package, with the rationale.
Do not improvise de-identification
Removing names alone is not a release decision. Record the approved process, required review and who may authorize deposit. Keep identifiers and credentials out of this worksheet.

Check the source

Step 3

Test a handoff, not a promise

Fictional example: a collaborator receives 'analysis_final.csv' but cannot tell whether a value of 999 means missing data or a measurement.

Make the package interpretable
Provide a data dictionary, missing-value definitions, a version identifier and code linking the file to the reported output. Ask a permitted colleague to reproduce one non-sensitive result.
Keep failures visible
Record the missing dependency or ambiguous field, its owner and the next check. A successful spot check is not evidence that the full dataset is error-free.

Step 4

Translate the plan into the actual funder requirements

NIH's format page says the 2026 DMS Plan format is required for applications and progress reports after its May 25 transition. From October 1, 2026, NIH no longer requires prior approval to change an approved DMS Plan; recipients report changes in the RPPR (Section C.5.c), and existing awards move to the 2026 format on the schedule in NOT-OD-26-100. NSF's PAPPG 24-1 Supplement 2 replaces the prior two-page-upload instruction with a Research.gov DMSP tool, released April 27, 2026. This worksheet is neither submission format.

Check the award and submission route
Open the current funder instructions and the specific solicitation. Record which form or system applies, the responsible approver and any project-specific requirements.
Make timing and retention explicit
Use the applicable release deadline, not a generic promise to share after acceptance. Identify the repository, review dependencies, retention requirement, costs and continuing owner. Resolve conflicts with the institution or funder before committing to a plan.
Record changes where the funder expects them
When the approach changes after award, update the worksheet and note which report carries the change. For NIH awards from October 1, 2026, that is the RPPR, Section C.5.c, not a prior approval request.

Check the source

Common questions

Can I submit this worksheet to NIH or NSF?

No. Use it to organize decisions, then complete the required current funder form or submission workflow.

Does FAIR require open participant-level data?

No. Authentication and authorization can be compatible with FAIR accessibility. The permitted access route still depends on the data, consent and applicable requirements.

How long should I retain the data?

There is no universal period in this guide. Record the requirement that applies to the award, institution, data and agreements, along with the responsible owner.

Sources and evidence

These checked sections support the specific statements identified below. The workflow and fictional examples are Manusights teaching material, not publisher instructions or evidence of institutional review. The check date is not a policy effective date.

What changed in this edition?

2026-10-01: Added NIH's NOT-OD-26-100 change: from October 1, 2026, changes to an approved DMS Plan are reported in the RPPR (Section C.5.c) instead of through prior approval, and existing awards move to the 2026 format. Rechecked the NIH, NSF and FAIR sources. The underlying worksheet PDF was not revised in this guide edition.

Recheck destination requirements before relying on them. Report a correction with the page, disputed statement and supporting source. Original Manusights educational text is available under CC BY 4.0 reuse terms; third-party material retains its own terms.

Research behind this guide

The sources above set the current rules. These peer-reviewed papers are the research to cite alongside them.

  1. Michener, W. K. (2015). Ten simple rules for creating a good data management plan. PLoS Computational Biology, 11(10), e1004525. https://doi.org/10.1371/journal.pcbi.1004525

    Ten rules for the plan that describes how data are treated during a project and what happens to them after it ends.

  2. Wilkinson, M. D., Dumontier, M., Aalbersberg, IJ. J., et al. (2016). The FAIR Guiding Principles for scientific data management and stewardship. Scientific Data, 3, 160018. https://doi.org/10.1038/sdata.2016.18

    The FAIR principles for reusable data, with specific emphasis on machines being able to find and use the data.

Cite this resource

Citation formats

Free to use and cite, with attribution. See the reuse policy for what you may republish.

APA
Manusights. (2026). Plan the data handoff before the project ends (Version 2026.10.01-guide2). https://manusights.com/resources/research-data-management-plan
MLA
Manusights. "Plan the data handoff before the project ends." Research Library, version 2026.10.01-guide2, Oct 1, 2026, https://manusights.com/resources/research-data-management-plan.
Vancouver
Manusights. Plan the data handoff before the project ends [Internet]. Version 2026.10.01-guide2. 2026 Oct 1. Available from: https://manusights.com/resources/research-data-management-plan

Next for the manuscript

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The right reporting framework makes the methods and evidence easier to review later.