As open as possible, as closed as necessary
An obligatory appendix to the application is the data management plan where you describe how you manage your research data and make them available after the project has been completed. Even if the project will not produce data to be stored or if it will use existing, openly available data, you should still append a data management plan to your application. In the appendix, describe your data management as briefly as possible. Answer the questions concisely and where applicable.
Draft the plan according to the structure below. You can use the data management planning tool DMPTuuli or draft the plan without it. The structure and contents of the appendix are the same regardless of which method you choose.
More guidelines on the details to be described in the plan are available in DMPTuuli and on the Academy of Finland’s website. Both of these sources include the same additional guidelines. DMPTuuli may also contain university-specific guidelines. The Finnish Social Science Data Archive (FSD) has also drafted its own guidelines as well as templates for data management plans.
- detailed Academy data management plan guidelines and best practices in DMPTuuli
- Academy of Finland's open science policy (see also Appendix 3 of the April 2017 call text)
- Finnish Social Science Data Archive: data management guidelines
Structure of data management plan
On the first page of the plan, write the applicant’s (the PI’s) name, research topic and application number. Also remember to date the plan. The length of the plan is 1–2 pages. Plans drafted with DMPTuuli are slightly longer than this, because of differences in text layout.
1. Types of data
What types of data (e.g. qualitative, quantitative, measurements) will the project collect or use? The data may be either new data or openly available data. What are the file formats of the data?
The data content is described in more detail in the research plan.
2. Documentation and quality
How will the data be documented? For example, what identifiers and metadata standard will be used? How will the quality of the data and the documentation be ensured?
3. Storage and backup
How will the data be stored and backed up during the whole life cycle of the research project (e.g. storage capacity and access to data)?
4. Ethics and legal compliance
How will ethical issues concerning data storage (e.g. sensitive personal information, third-party access to data) be taken into account? How will copyright and IPR issues be managed?
Please note that the ethical issues that concern data collection and research implementation are described in the research plan.
5. Data sharing and long-term preservation
How and when will the data be made available for reuse by other researchers? With what party (data archive, storage service, etc.) will you collaborate to manage the data and make them available? What resources will enable data sharing and long-term preservation?
For each of these sections, we have posted the detailed Academy’s guidelines and tips for best practices in DMPTuuli on our website: Detailed Academy data management plan guidelines and best practices in DMPTuuli.
Updated for April 2017 call on 7 March 2017.