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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.

Guide contents


  • General information about Data Management Plans (DMP) and DMPTuuli tool

1. General description of data

  • This page aims to give you an idea on questions in DMPs such as what data will be collected, produced or reused, what file formats will the data be in, or how will the consistency and quality of data be controlled?

2. Ethics and legislation

  • Information about ethical compliance and data ownership

3. Documentation and metadata

  • How will you document your data to enable it to be discovered, used and properly cited, and what kind of metadata standards will you use?

4. Storage and backup

  • Information about storing and backing up your data, and controlling who has access to it (data security)

5. Open and publish

  • Consider and explain what parts of your data can be opened. Where will you archive your data?

6. Responsibilities and resources

  • Information about data management responsibilities and resources

Research Data Management (a separate guide)

  • General and practical information about research data management, and how to open and store your research data

Contact information

The library provides support to creating data management plans (DMP) and managing and describing data throughout its life cycle. The easiest way to contact us is by e-mail:

Maaria Harviainen, information specialist
tel. 040 710 4225

Harri Ollikainen, information specialist
tel. 050 477 5445

Sections from Jyväskylä University DMP guide has been used on these pages, licensed under a Creative Commons Attribution 4.0 International License

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. See also DMPTuuli's various templates and instructions relevant to different funders, research organizations and data types.

A research data management plan includes:

  1. General description
  2. Ethical principles regarding personal information and legal issues relevant to data ownership and rights
  3. Documentation and metadata
  4. Storing and backing up of the data
  5. Opening, publishing and archiving the data after the research project
  6. Responsibilities and resources

Attach the plan (1-4 pages) to your research plan or 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 but not limited to:

  • 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)
  • the digital representation of the research material (such as images, transcriptions, sound and video recordings)
  • research sources (such as archive material)
  • source code and software 

Example DMPs

DMPs from different fields of science for comparison. Note that public DMPs in e.g. DMPTuuli have not been vetted for quality.

Information elsewhere

More information about DMPTuuli

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