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DMPTuuli guide: Home


This guide provides information about DMPTuuli tool, and how you can use it in writing a data management plan. The structure of the guide follows the structure of the general DMPTuuli template.

For more information about research data management, and how to open and store your research data, see the Research Data Management guide.

What DMPTuuli?

DMPTuuli is a tool for researchers with which you can write data management plans (DMP). It can be used while writing the research plan or funding apllication, and to support research data management (RDM) at various stages of the research process.

With DMPTuuli researchers are able to plan their data management in a structured manner. Within DMPTuuli you can find various templates and instructions relevant to different funders, research organizations and data types.

A research data management plan includes:

  • General description
  • Ethical principles regarding personal information and legal issues relevant to data ownership and rights
  • Documentation and metadata
  • Storing and backing up of the data
  • Opening, publishing and archiving the data after the research project
  • Responsibilities and resources

Attach the plan (1-2 pages) to your funding application.

If your research doesn't produce new data that can be archived or the data that's being used is already open, even then describe the data briefly and attach it to your application. All in all, answer the questions if and when they are relevant to your research and research data. If you only use data that is already openly available, you don't have to save or archive it again.

If your data is confidential and cannot be opened, you can mention this in the attachment. The description of the data (metadata) should however be recorded in a national or international data repository.

Why DMP?

Why should you manage your research data and write a data management plan (DMP)?

  • Research data management and its planning are an integral part of good research practices.
  • You will reduce the risk of losing your data.
  • You will be able to anticipate complex ownership and user rights issues in advance.
  • It helps you support open access to create productive future collaborations.
  • You will meet funder requirements.
  • It helps you save time and money.

A clearly written data management plan supports the principles of open science and contributes to the creation of new innovations and ideas, and fruitful collaboration.

Your DMP should describe how you manage data during as well as after the research project. The plan should be updated as the research project evolves.

Your research data management practices should follow the FAIR principles, which require that your data will be Findable, Accessible, Interoperable and Re-usable.

In the DMP data is understood as a broad term including:

  • data collected by various methods (such as surveys, interviews, measurements, evaluations, audio visual materials, diaries etc.)
  • data produced during the research (such as analysis results)
  • research sources (such as archive material)
  • source code and software 

Information elsewhere