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Research Data Management

Data management plan (DMP): what, why, and how?

A written data management plan (DMP) is an important part of research data management, an essential tool for following good research practices and opening up your data. A researcher carrying out research should create a DMP before he/she starts his/her research project, and update it when necessary during and after the research project. It is a living document that accompanies the whole research life cycle, even after the active phase of the research project.

A DMP is a document completing your research plan. You can refer from one document to the other in order to avoid overlap between them. Introduce data analysis and other methods in your research plan.

The DMP ought to cover the collection and processing of data, ethical compliance, ownership and rights to use, short-term storage and backup, long-term preservation and reuse, planned disposal and the associated resource needs. More information, see DMP guides and checklists in the section below.

See the video guide Introduction to data management planning by CSC. 

Use Hanken's DMP template or other Public DMP templates (with Hanken's DMP guidance integrated) in DMPTuuli to help you write and update a DMP. See DMPTuuli with Hanken's DMP guidance and DMP template in the next section.

DMPTuuli with Hanken's DMP guidance and DMP template

DMPTuuli logo

The tool DMPTuuli is helpful when writing, updating, reviewing and sharing your data management plan. DMPTuuli is part of the Open Science and Research (ATT) project, maintained by CSC, launched and funded by the Ministry of Education and Culture. It offers a Finnish national central channel for guidance and support for writing a DMP at all stages. The tool is based on an open source solution and any individual researcher can register and create an account to use it freely.

Hanken's DMP guidance and Hanken's DMP template are both integrated in DMPTuuli:

1. DMP guidances in DMPTuuli:

DMPTuuli contains useful advice and tips for all organizations and all types of applications, including:

To get access to Hanken's DMP guidance in DMPTuuli, follow the following steps:

- Open DMPTuuli and register an account.

- Click “Create plans” on the left upper side. Fill in the information about your research project, and make sure that "Hanken School of Economics" is selected as the primary research organization. A funder's DMP template will be available after the funder is selected under "Select the primary funding organisation." Then click "Create plan."

Create plans in DMPTuuli

- Next, under "Select Guidance" on the right side, remember to choose "Hanken School of Economics" and click "Save."

- Then under "Write Plan," within each section of a DMP, the content of Hanken’s specific guidance on each topic will show after you click "Hanken" and then "expand all" or the sign "+":      

Expand all in DMPTuuli

- Do not forget to click “Save” after you finish answering each section.  


2. DMP templates in DMPTuuli:

You can find various Public DMP templates to meet the specific funder requirements on DMPTuuli pages. 

Hanken's DMP template has also been integrated in DMPTuuli. When creating a new DMP, select “Hanken School of Economics” as the primary organisation. Then remember to choose ”No funder associated with this plan or my funder is not listed.” This is especially for research projects which do not have any funders associated or the funders are not listed. Hanken’s DMP template will be available after you click “Create plan.”

No funder in DMPTuuli

Now you can write a DMP under “Write plan” by using Hanken’s DMP template. After clicking each “+” sign, you can see the content and complete the sections of a DMP. Use Hanken's DMP guidance on the right side to help you to complete each section. Remember that the content of Hanken’s specific guidance on each topic will only be shown after you click "Hanken" and then "expand all" or the sign "+" on the right side.      

Do not forget to click “Save” after you finish answering each question. 

DMP guides and checklists

Although there may be some differences depending on research domain, in general, a good data management plan will address the following seven aspects:

1. General description of data: Data types and formats, estimated data size, and how to control the consistency and quality of data.

Note that it is important to identify all sensitive, personal, and confidential data types to ensure that sufficient data protection measures are taken and the risks involved are minimized. 

2. Ethical and legal compliance: Describe how you will maintain high ethical standards and comply with relevant legislation when managing your research data. What are the risks involved, and how are they managed?

  • Ethical concerns: eg., how to handle sensitive and personal data, how to gain data-sharing consent from research participants, when and how to apply for an ethical review, and research ethics. See Handling personal data in research and Ethical review.
  • Legal issues: eg., data protection policy, data-sharing agreements, data ownership, open data licenses, secondary data usage copyright permissions and other Intellectual Property Right (IPR) issues. See Legal compliance

3. Documentation and metadata: How to describe your data to make them findable, accessible, interoperable, and reusable (FAIR) for you and others. See Data documentation and metadata.

4. Data storage and backup during the research project: Where and how to store and back up your data, data security, and access control. See Data storage and backup.

5. Data publishing and sharing after the research project: What part of the data to be made openly available or published, where and when to make the data or their metadata publicly available. See Data sharing and preservation.

Note that data with personal information can only be published anonymised. Pseudonymised data is still personal data, and therefore cannot be opened without explicit consent for that purpose. Se Anonymisation and Personal Data by Finnish Social Science Data Archive (FSD).

6. Defining roles and responsibilities of research team members: Who are responsible for data management tasks including data protection, information security, data documentation, data archiving and publishing? 

7. Estimating resources required for data management: Time, workload, and possible costs. See Costs of data management by Utrecht University.


Use Hanken's DMP template or other Public DMP templates (with Hanken's DMP guidance integrated)  in DMPTuuli to help you write and update a DMP (See DMPTuuli with Hanken's DMP guidance and DMP template above).

More information about how to create a DMP, see: