Research data
FAIR Research Data: A Simple Data Management Plan Before You Collect
Plan research files, documentation, access and preservation using FAIR principles without assuming all data must be public.
Decide how data will be named, documented, protected and preserved before collection. FAIR means findable, accessible, interoperable and reusable; access can still require authorisation.
For Indian research teams, check your university, ethics committee and receiving journal requirements alongside this workflow.
Turn FAIR into project decisions
GO FAIR describes principles for making digital assets findable, accessible, interoperable and reusable. These include persistent identifiers, useful metadata, access protocols, provenance and clear usage licences. Access can involve authentication and authorisation. FAIR does not require indiscriminate public release. The FAIR principles.
Our proposed starter plan asks six questions: What will we collect? Where will it be stored? How will we describe it? Who may access it? What can be shared? Who will preserve it? Answer them with the supervisor or project team before data begins accumulating across devices.
Make files understandable to another researcher
Choose a consistent naming convention and keep an untouched copy of original observations. Separate raw, cleaned and analysis files. Write a README that explains the purpose of each folder, the collection period, software requirements and the route from inputs to results.
A small data dictionary can record each variable's meaning, units, allowed values and missing-value codes. Document transformations and the reason for exclusions. The following is an illustrative folder structure, not a requirement:
project/
raw/ original inputs, restricted if needed
processed/ documented transformations
analysis/ scripts and environment notes
outputs/ figures and tables
README.md how the pieces connectSomeone should be able to understand the structure without reading your private messages or guessing which file is final.
Plan protection and sharing together
Decide which team members need access and use institution-approved storage. Agree backup and recovery responsibilities. Do not assume that a personal cloud account is suitable for participant data. Sharing decisions must follow consent, ethics approval, agreements and applicable requirements.
Prepare separate public and restricted material where appropriate. Remove sensitive information from public metadata as well as files. Record any access-request procedure clearly. Check ownership before choosing a licence: an open licence cannot grant permissions you do not hold.
Choose a preservation route
Before depositing material, check a suitable disciplinary or institutional repository's accepted formats, access controls, identifiers, retention commitments and costs. A repository entry should explain what the files contain and how they relate to the paper or project. Uploading a folder without documentation does not make it reusable.
- Assign a responsible owner for the plan.
- Document file formats, variables and transformations.
- Check access and consent constraints.
- Test the backup process.
- Select a repository and describe the deposited version.
- Review the plan when the project changes.
Takeaway: start with a plan you can maintain. A clear README and agreed responsibilities are a practical beginning, not a certification that a dataset satisfies every FAIR principle.
Sources & editorial scope
Official sources checked on 5 October 2026. This article combines attributed guidance with ScholarVault’s suggested workflows and fictional examples. Requirements can change; check the receiving organisation’s current policy. No endorsement of ScholarVault by these organisations is implied.