Research Council of Finland DMP

Management of research data and drafting a data management plan are parts of good scientific practices.

The data management plan is a living document which should be updated throughout the research process. In it:

• You describe how you will manage the research data throughout its lifecycle.
• You explain what will happen to the research data after the research is complete.

To create your data management plan, use DMPTuuli, a tool recommended by the Research Council of Finland for writing data management plans. The data management plan for the Research Council of Finland should be no more than 3 pages long.

NB! Please use the template: Data Management Plan - Research Council of Finland in DMPTuuli. If you use an old DMP as a foundation for the current one, please make sure it is in the same format.

In addition to this guide, you can find Turku University guidance also in DMPTuuli and other Turku University guides.

• DMP Tuuli tool
• Guidelines provided by the Research Council of Finland integrated into the DMPTuuli tool
• National guidelines for assessing data management plans are available on Zenodo
• Research data lifecycle guide of the University of Turku

Research data is data created during the research process, or it can be previously gathered data used in the research. Research data can be used to justify or reproduce research results. Different kinds of research data include for example:

• different measurement results
• data generated from surveys and interviews (questionnaires, responses, tables, other numerical data, etc.)
• text materials (transcribed text files, corpus linguistics, discourse analysis, stylistics, etc.)
• audio recordings (interview studies, phonetics, discourse analysis, conversation analysis, etc.)
• other audio recordings (e.g., music)
• video recordings (e.g., interview studies, media studies, sign language)
• data collected through observation (observation matrices, observation diaries, etc.)
• research diaries kept by participants
• research diaries
• researcher’s notes
• self-made software and source codes
• physical or electronic source materials collected by the researcher (e.g., biological samples, artifacts, text samples, collection materials)
• new data created by the researcher based on other data