What is research data management (RDM)?

What is research data management (RDM)?

Research data are at the heart of research design. Data management at the Ģ��ֱ�� ensures the widest possible transparency, discoverability, accessibility, usability and, where possible, open re-use of research data. Well implemented data management is part of modern, responsible science and supports both the researcher and the organisation in carrying out research tasks.

Good management of research data aims to ensure that the research data and related descriptive information (documentation and metadata) is produced in such a way that the information it contains remains usable and reliable, and that its data protection and security are ensured. With well-managed and organised data, research is of higher quality and, above all, reproducible. Good data management is also a prerequisite for the transparency of research data. However, data management applies to all research, including research that does not aim to make research data open.

Life-cycle thinking is a key element in the management of research data. Research data are generated in a controlled way and the way they are used, managed and, at the end of the research, opened, archived or destroyed is planned from the outset.

In practice, the need for data management arises from three sources: legislation, the requirements of funders and universities, and the conduct of the research itself.

Jurisdiction specifically regulates the processing of personal data in the course of research. Informing research subjects in the way required by law and good scientific practice requires careful planning of the research, data handling and its life cycle. The issues of minimising the processing of personal data, safe storage, anonymisation and possible opening or archiving require special attention.

In addition, there may be legal issues related to the ownership, copyright and use of research data. A key part of good data management is to be aware of these as well and to ensure that rights are transferred to the rightful owner - preferably an organisation.

All major research funders base their funding conditions on the assumption that good data management is a prerequisite for modern scientific practice. The Ģ��ֱ��'s research data policy also assumes that good data management is at the heart of all research.

Among the funders, the Research Council of Finland and the EU also start from the principle that research data should be as open as possible. The principle of "as open as possible, as closed as necessary" has also been adopted in the Ģ��ֱ��'s Data Policy. Unless there is a specific reason, research data should be open. In order to open up the data and to make it understandable to others when opened up, good data management and planning is again needed at the early stages of the research. The most appropriate level of openness must be found for each data set, from opening up metadata to open access at file level on the web.

A data management plan is often drawn up for funders, demonstrating both commitment to the funder's requirements and the ability to meet those requirements. A resource management plan is also a mandatory annex when applying for an ethical peer review.

Funders' and universities' requirements for materials management follow the so-called FAIR principles, which require that materials be discoverable, accessible, interoperable and reusable.

Research Data Policy of th Ģ��ֱ��

Conducting the research itself also requires comprehensible, well-organised and accessible data. In addition, the data must be able to be stored and distributed securely. All of this is made possible by good data management and design.

Good data management also enables research data to be opened up when required by a funder or publisher. Good data is a scientific and professional asset for its author.