When developing your research plan, you should also create a written data management plan (DMP). The DMP is a tool for ensuring good research practices. It helps the researcher to avoid risks (e.g. in relation to data protection and property rights) and helps to protect the research material from misuse. Several major research financiers require submitting a DMP during the application stage. The DMP is a living document that should be updated during the course of the research project.
A DMP consists of an overview of the project, how data is collected, handled, organized, saved, and archived for continued use. A DMP is also a tool for the researcher. The plan helps the researcher to formulate questions, which need to be solved during the project.
As Arcada promotes open science and research, it should be possible to reuse the material in future research, whenever applicable. The FAIR principles serve as a starting point: Findable, Accessible, Interoperable and Reusable. This means that the data is easy to find and easy to access, that both data and metadata are standardized, and that the data can be reused in the future. Fair Principles (fairdata.fi).
At Arcada we use the tool DMPTuuli for creating a DMP. It is an online and user-friendly tool, maintained by CSC and funded by the Ministry of Culture and Education. It offers support for all stages of your DMP as well as for when you apply for funding. On DMPTuuli you can share your plan for commenting or cowrite a plan with a fellow researcher.
On the DMPTuuli website there is a short video with instructions (2:41) on how to get started with the program: https://dmptuuli.fi/help. The video is in Finnish with English subtitles. You can log in to DMPTuuli with your HAKA username and password. Add your ORCID identification code to your personal details on DMPTuuli. The first time you log in, click Create Account and enter Arcada as your organization.
On DMPTuuli you can find guidelines from several different research funders regarding their requirements for your DMP.
If you need help with your DMP – contact datamanagement@arcada.fi.
In general, a good data management plan will address the following seven aspects (allowing for some variation depending on research domain):
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?
3. Documentation and metadata: How to describe your data to make them findable, accessible, interoperable, and reusable (FAIR) for you and others. See Metadata and data documentation.
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, backup and transferal.
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 publishing and preservation.
Note that data with personal information can only be published anonymized. Pseudonymized 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.
For more information about how to create a DMP, see: