Research is guided by good scientific practice, the key operating principles of which include diligence and accuracy in research work and the recording of research results from planning to implementation. This also includes the requirements of good scientific practice for research data and its management: High-quality and reliable research is based on accurate and comprehensive research data, the management of which is well planned and carefully implemented.
The importance of data management has been emphasised in research organisations in recent years. Many organisations have a research data policy that provides guidelines on the policies and responsibilities of research data management. According to the Publication and data policy of UEF, a data management plan should be created during the planning phase of research. In addition, many research funders require a data management plan (e.g. the Academy of Finland).
Data management practices
Data management ensures high-quality and reliable research results, minimises risks and enhances the reuse of data. Thus, data management includes measures to ensure that the research data and the associated metadata are easily discoverable, interpretable, usable and appropriately protected throughout the life cycle of the data. It is advisable to keep in mind that the life cycle of research data may be hundreds of years longer than the life cycle of the research project that originally produced the data in question. Moreover, the subsequent user of the data may be, for example, a teacher or an authority instead of a researcher.
Practical measures in data management include defining user rights, applying for the necessary permits or statements, backing up, documenting procedures, publishing the data or making them fit for the needs of a specific data archive. For more information about these actions, see the different sections of this website, which also provide tips and links to additional information outside of these websites.
Benefits of data management in a nutshell
Investing in data management planning brings many benefits:
- Quality: The research material remains accurate and comprehensive when, for example, files and folders are clearly named and different versions are saved and named logically.
- Legislation: Data management planning guides you to consider, for example, the requirements of data protection legislation.
- Risk management: The risk of sudden destruction of research material is reduced as data security and backups are managed systematically.
- Meeting requirements: data management makes meeting the requirements of the funders and the policy of the research organisation easier.
- Resources: Time and other resources will be saved as the research process progresses.
- Transparency in science: Storing research data in a repository secures the research output and enables it to be made open for others to use.
- Merit: Making high-quality research data available to others increases the impact of research and promotes new and interdisciplinary cooperation opportunities.
- Competence: Data management skills can also be utilised outside research as general information management skills.
More information, sources and links
Colavizza G, Hrynaszkiewicz I, Staden I, Whitaker K, McGillivray B (2020). The citation advantage of linking publications to research data. PLoS ONE 15(4): e0230416. Pysyvä tunniste <https://doi.org/10.1371/journal.pone.0230416>.
The Finnish Code of Conduct for Research Integrity and Procedures for Handling Alleged Violations of Research Integrity in Finland 2023. Publications of the Finnish National Board on Research Integrity TENK 2/2023. Helsinki: Finnish National Board on Research Integrity TENK, 2023.
Popkin, G. (2019). Data sharing and how it can benefit your scientific career. Nature Careers feature 569: 445-447. Pysyvä tunniste <https://doi.org/10.1038/d41586-019-01506-x>.