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Data management

Data management

Data management refers to the planned collection, organization, storage and description of research data so that materials remain useful and reliable throughout the research process. Good data management enables the opening of research data for further use. Researchers should follow good data management practices, which include security and data protection in accordance with legislation and research integrity.

FAIR principles

Data management practices should seek the compliance with the FAIR principles, ensuring that the data is

  • Findable,
  • Accessible,
  • Interoperable and
  • Re-usable.

This is ensured, e.g. with persistent identifiers (e.g. DOI, URN, ORCID), open file formats, clear definition of ownership, terms and licenses, and rich description of content, structure and permissions of the material (rich metadata). Learn more about FAIR principles and the Policy for Open research data and methods.

FAIR periaatteet; Find, Access, Interoperate, Reuse

Source: SangyaPundir, Wikimedia Commons. CC BY-SA 4.0.

The life cycle of research data

This guide provides guidance on the planning of data management, including information on the storage, description and opening of research data. The guide also examines the ethical and legislative issues of the materials and compiles information on data management guides and support services. The aspects of data management are presented in three phases (at the beginning, during and end of research) based on the life cycle of the research data. It is good to familiarize yourself with each step at the beginning of the research when preparing a research data management plan. This will ensure that data is well managed from the beginning. Well designed is half done!


Source: FSD. Data management guidelines.


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