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Research Data Management: Plan

Data Management Plan

Data Management Plan (DMP) is a document to which you, as a researcher or working in a development and innovation project, define the life cycle of your data during and after your project. The open science policy of the Tampere Higher Education Community requires researchers to draw up a data management plan for their research already at the planning stage. The contents of the data management plan should also be updated as things become more specific or change as the research progresses.

How to write a DMP? - READ THIS FIRST!

  • Use DMPTuuli to draft your data management plan. DMPTuuli hosts updated funder templates and guidance. You can also find Tampere higher education community's DMP guidance in the tool.
  • Use a data management plan to complement your research plan.
    • Research plan describes the scientific, analytical and methodological processing of data.
    • Data management plan describes technical and administrative management of data.
    • To avoid redundancy, refer to your research plan in your DMP and vice versa.
  • Use DMP as a risk evaluation document. Demonstrate that you can identify, anticipate and handle the risks related to your data management workflows.
  • Draw up a data management plan from the perspective of your own research project. Do not copy examples from elsewhere.
  • Write only sentences you yourself understand.
  • Answer the questions where applicable - If a certain question is not applicable in your case, justify why not.
  • Answer at least the main categories.
  • Include background information such as the name of the applicant and the project, project number, funding programme, version of DMP.
  • Follow your home institution’s and research funder’s data management guidelines.

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

  • It is good research practice!
  • 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 research data and meet funder requirements on data management.
  • It also helps you create productive future collaborations.
  • Planning helps you save time and money.
  • Your DMP reflects your managerial skills as a project leader.

In the DMP context, data is understood as a broad term. Data covers all information and material your research results are based on. You can concentrate on the data that is your responsibility.

Your DMP should describe how you will manage data during the whole research life cycle. The DMP is a living document that should be updated as the research project progresses.

Your research data management practices should aim to produce reusable (meta)data that follows the FAIR principles, that is, your (meta)data will be Findable, Accessible, Interoperable and Re-usable.

The contents of the data management plan can be presented in various ways. In the following table we have listed 6 components of DMP as defined in the General Finnish DMP Guidance 2021.

DMP components

DMP components
DMP questions
General Description of Data
  • What kinds of data is your research based on? What data will be collected, produced or reused? What file formats will the data be in? Also give a rough estimate of the size of the data produced/collected.
  • How will the consistency and quality of data be controlled?
Ethics and Legal Compliance
  • What legal issues are related to your data management? (For example, GDPR and other legislation affecting in data processing.)
  • How will you manage rights of data you use, produce and share?
Documentation and Metadata
  • How will you document your data in order to make it findable, accessible, interoperable and re-usable for you and others?  What kind of metadata standards, README files or other documentation will you use to help others to understand and use your data?
Storage and Backup during the Research Project
  • Where will your data be stored, and how will it be backed up?
  • Who will be responsible for controlling access to your data, and how will secured access be controlled?
Opening, Publishing and Archiving the Data after the Research Project
  • What part of the data can be made openly available or published? Where and when will the data, or its metadata, be made available?
  • Where will data with long-term value be archived, and for how long?
Data management responsibilities and resources
  • Who (for example role, position, and institution) will be responsible for data management (i.e. the data steward)?
  • What resources will be required by your data management to ensure that data can be opened and preserved according the FAIR principles (Findable, Accessible, Interoperable, Re-usable)?

Help and guidance

Use DMPTuuli to draft your data management plan. Tampere higher education community's DMP guidance can also be found from DMPTuuli.

General guidelines

Contact us

Is there something you did not found in this guide? Or is some important information missing? You can always contact us for further information, and we will help you with the research data management.

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Budget

Estimate the resources, such as time and financial costs, needed to manage, share and preserve the data. These may include storage costs, hardware, staff time, the costs of preparing data for deposit and repository charges.

Putting data into a usable format and making it meaningful to other researchers takes time and costs money in terms of software, hardware, and personnel. Start planning your data management already in the beginning of the project, and you will save time and effort when you are sharing and preserving your data.

Tips for best practices

  • Consider, if there will be additional costs from computational facilities or resources that need to be accessed. Consider costs (time and financial) e.g. from
    • software
    • higher level of security for activities and solutions
    • anonymizing personal and sensitive data
    • metadata production
    • transcription service
  • Account for resources, time and money, needed to prepare the data for sharing it and preservation (data curation).
  • Specify your data management costs in the budget, according to funder requirements. Remember that basic level institutional IT-services are usually regarded as overheads in the budget.

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