Data management planning
Data management planning is a key process in planning your research. In this section, we first present the main stages of the research data management planning process, with references to appropriate subpages and external links, and then discuss in more detail, how to document this process in a data management plan. The Principal Investigator (PI) is responsible for making decisions on data management and open access to research data.
Typically, a data management plan addresses questions such as
- How the project proposes to collect data and use existing data
- The methodologies and standards that will be applied
- How the data will be curated and preserved
- The ownership and user rights of the data used or produced by the project
- How the data produced will be open for use by other researchers during the project and after its conclusion
- Research ethics
Informed consent of human subjects to research is an essential part of data management. The appropriate anonymisation of personal information enables the opening of otherwise confidential research data. Make sure to prepare the description of the registration of personal information. Read more about the handling of personal data in the section Research ethics.
Data management plan (DMP)
A data management plan is a key instrument for
- Planning the data lifecycle
- Specifying data ownership and user rights
- Defining who has access to data during and after the project
- Identifying information security and research ethics issues
Writing a data management plan is not just a formality. The plan is a reference document for everyone working on your project - make sure that you follow and revise it during your work, and when finishing a project.
An increasing number of funding agencies require a data management plan from the sponsored projects. For example, in the Horizon2020 programme of the European Commission, a DMP is an obligatory deliverable during the first 6 months of all projects that take part in the Open Data pilot. As of the 2017 Work Program, research data is open by default. In the proposal stage, the principles of data management in the project need to be explained in the work plan, and the necessary resources outlined. The Academy of Finland and Business Finland (formerly Tekes, the Finnish Funding Agency for Innovation) require a data management plan as part of the funding application.
DMPTuuli: data management plan builder
DMPTuuli is a web-based data management planning tool that helps researchers to create data management plans that meet the demands of the prominent funders in the Finnish research context.
All researchers in Finnish universities and research institutes, as well as their associates have the right to use DMPTuuli. There is a four-minute video explaining DMPTuuli before logging into the system.
DMPTuuli integrates Finnish funder-specific guidelines to generate a plan for the European Commission Horizon2020, Academy of Finland, and Business Finland. Several organisations have produced additional guidelines. For example, when creating a new plan in DMPTuuli, you can receive detailed guidance by clicking 'FSD (Tietoarkisto) guidance' at 'Tick to select any other sources of guidance you wish to see'.
Creating a data management plan yourself
You can also write a DMP using any word processing software. Aalto University provides a template (example attached below)for writing data management plan for Academy of Finland projects. To support the writing, you can also use the file Tuuli Checklist and Guidance (attached below) courtesy of University of Helsinki. The Tuuli checklist and guidance advises what to take into account when planning data management in any research project, regardless of the funders' requirements. In addition, University of Helsinki has published an example for a Data Management Plan.
When writing a DMP, you will be asked the file formats you intend to use. Read more about file formats.
When writing a DMP, you will be asked the metadata model you intend to use. Metadata describes research data. To achieve interoperability and findability of research data, it is important to use standard international metadata models, such as Data Documentation Initiative (DDI) or CERIF. Read more about metadata.
- Make your data FAIR: findable, accessible, interoperable and reusable.
- Look for instructions/templates from your funding agency, and/or use the template or DMPTuuli.
- Select an intended data repository, and the repository guidelines will offer you options for metadata, file formats, and licenses needed to use that repository. Some repositories, such as FSD, offer services and personal guidance, and it is helpful to contact them in the planning stage.
- Open Science and Research Initiative (Avoin tiede ja tutkimus):
- European Commission
- Discussion on FAIR data principles
- Academy of Finland:
- Finnish Social Science Data Archive Data Management Guidelines
- University of Helsinki has published an example for a Data Management Plan
- DMP checklist (Data Curation Centre)
- Search for funder requirements for data archiving in SHERPA/JULIET