Reference notes
Coverage
Files · documentation · storage · security · ethics · sharing · preservation · roles
Sources
NIH · NSF · UKRI · Digital Curation Centre · FAIR principles · re3data
Last reviewed
August 2026
Prepared by the Manusights editorial team.
Project-planning checklist
Make the data plan before the files become difficult to manage
A data management plan explains what the project will create, how the team will keep it understandable and secure, and what will happen when the project ends.
Use this checklist before collection begins, then revise it when the methods, team, risks, funder requirements, or repository plan changes. Your institution's policy, ethics approval, contracts, and funder template always take priority.
The six-part planning worksheet
Answer each question with a named system, person, rule, or date wherever possible.
1. Data and formats
- What data, code, images, recordings, samples, or documents will the project create or reuse?
- Which file formats are required during analysis, and which open or preservation-friendly formats can be retained?
- How much storage will the project need, including working copies, backups, derived data, and final deposits?
2. Organization and documentation
- What folder structure and file-naming convention will the team use?
- How will versions, processing steps, exclusions, and changes be recorded?
- Which README files, codebooks, data dictionaries, protocols, and metadata standards will another person need?
3. Storage, backup, and security
- Where will active files live, and which institution-approved systems are required?
- How often are backups created, how are they tested, and who can restore them?
- Which data need encryption, access controls, audit logs, secure transfer, or separation of identifiers?
4. Ethics, rights, and access
- What consent, ethics-review, contractual, Indigenous-data, privacy, or legal conditions govern the data?
- Who owns the data and code, and who may authorize access, reuse, licensing, or disposal?
- What can be shared openly, what requires controlled access, and what cannot be shared?
5. Sharing and preservation
- Is there a trusted subject repository, institutional repository, or appropriate general repository?
- What will be deposited, under which license, with which metadata, and on what timetable?
- How long must the data be retained, and what will happen to temporary, sensitive, or non-preserved files?
6. Roles, resources, and review
- Who is responsible for documentation, access approval, quality checks, backup monitoring, deposit, and plan updates?
- What staff time, storage, repository, de-identification, transcription, or preservation costs belong in the budget?
- When will the team review the plan, and what project changes require an immediate update?
Repository decision
Choose the destination before the deadline
A repository is not just a file drop. Check fit, access, documentation, identifiers, preservation, and policy before promising where the data will go.
- 1
Use a subject repository when one fits
Discipline-specific repositories often provide the metadata, file checks, community standards, and discovery routes your data needs.
- 2
Check institutional options
Your university may provide a repository, storage, preservation, DOI, or controlled-access service with local support.
- 3
Evaluate a general repository
When no subject or institutional option fits, compare general repositories for identifiers, licenses, access controls, preservation, costs, and size limits.
- 4
Record the decision
Name the repository in the plan, confirm it accepts the data type, and document any deposit timing, access, or cost constraints.
A useful plan is operational
Weak: Data will be stored securely and shared when possible.
Stronger: The project manager will store coded working data in the institution-approved research drive, limit access to named study staff, review permissions quarterly, and deposit the de-identified analysis dataset with its codebook after the primary paper is accepted, subject to the consent and ethics terms.
Use enough detail that a new team member can follow the plan and a reviewer can see how the promises will be carried out.
Review the plan at real transition points
- Before data collection, acquisition, or reuse begins.
- When a new collaborator, site, vendor, or data source joins the project.
- When consent, ethics, security, or contractual conditions change.
- Before a grant report, manuscript submission, repository deposit, or team handoff.
- At project close, before accounts expire or staff leave.
Primary and established guidance
NIH DMS Plan guidance
The official NIH elements and expectations for writing a Data Management and Sharing Plan.
NSF PAPPG
Current NSF proposal policy, including data-management-plan requirements and related proposal instructions.
UKRI research data guidance
UKRI expectations for responsible management and open access to research data.
Digital Curation Centre
Practical guidance and a planning checklist for developing a data management plan.
FAIR Principles
An accessible explanation of making data findable, accessible, interoperable, and reusable.
re3data
A registry for discovering and comparing research data repositories across disciplines.
Related guides in this collection
Plan for data sharing
Review repositories, data-availability statements, FAIR principles, and major funder expectations.
Plan a literature search
Document concepts, queries, databases, limits, dates, and results from the start.
Find the reporting guideline
Match the study design to the appropriate reporting framework before writing the final paper.