What is it? Why is it important?

The Data Management Plan (DMP) is a formal document that describes how data is handled during study conduct and after the study has been completed.

The aim is to offer long-term perspectives on:

  • How data is documented, collected, derived, and validated
  • How data is preserved with long-term access to data and metadata
  • Data relevance and understanding, including data sharing for future use

DMPs will increasingly standardise data handling practices and allow for the reproducibility of research results.


The ability to openly share research data is the main principle of good scientific practice. This should be defined in the DMP.

Health-related data is sensitive data. Consequently, data protection laws, including ethical and confidentiality issues must be considered when sharing this type of data.

What do I need to do?

Questions to address when writing the DMP:

  • What type of data (variables) is collected?
  • How will data be collected or created?
  • What documentation and type of metadata is included?
  • How is data access and security managed?
  • How are ethical issues and the use of sensitive data handled?
  • How is data stored?
  • What are data back-up procedures?
  • How and where is data shared?
  • How is data archived upon study termination?
  • How are copyright intellectual property issues handled?

The DMP should be written:

  • In collaboration with the data manager of your study
  • Prior to study conduct, as it might be required during grant applications (e.g. SNSF, regulatory institutions)

Where can I get help?

Your local CTU can support you with experienced staff regarding this topic

External Links

SNSF – see in particular

  • Data Management Plan – DMP guidelines for researchers

NSF – see in particular

  • Data management preparations – DMP general guidelines
  • CTU – Clinical Trials Unit
  • DMP – Data Management Plan
  • NSF – National Science Foundation
  • SNSF – Swiss National Science Foundation
Development ↦ Data Handling ↦ Data Quality ↦ Data Mgmt. Plan

Provides some background knowledge and basic definitions

Basic Protocol
Basic Statistics
Basic Monitoring
Basic Drug or Device
Basic Biobanking

Starts with a study idea

Ends after having assessed and evaluated study feasibility

Concept Protocol
Concept Statistics
Concept Drug or Device
Concept Biobanking

Starts with confidence that the study is feasible

Ends after having received ethics and regulatory approval

Development Protocol
Development Statistics
Development Drug or Device
Development Biobanking

Starts with ethics and regulatory approval

Ends after successful study initiation

Set-Up Protocol
Set-Up Ethics and Laws
Set-Up Statistics
Set-Up Quality and Risk
Set-Up Drug or Device
Set-Up Biobanking

Starts with participant recruitment

Ends after the last participant has completed the last study visit

Conduct Protocol
Conduct Statistics
Conduct Drug or Device
Conduct Biobanking

Starts with last study visit completed

Ends after study publication and archiving

Completion Protocol
Completion Statistics
Completion Drug or Device
Completion Biobanking
Current Path (click to copy): Development ↦ Data Handling ↦ Data Quality ↦ Data Mgmt. Plan

Please note: the Easy-GCS tool is currently under construction.