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FAIR principles

tekijä: timapupu Viimeisin muutos tiistai 29. kesäkuuta 2021, 15.30

For research data, you can ensure compliance with the RCR by following so-called FAIR principles as closely as possible: 

  • Findable: The research data are described with comprehensive metadata. The metadata can be published on a search engine, where they are provided with a permanent identifier. In some situations, the actual data can also be published.
    • Metadata is a set of data that describes other data, in this case: data on your research data. Metadata include, for example, the name given to the data as well as when and how the data were collected. More on metadata later. 
  • Accessible: The research data or at least their metadata are accessible. Accessibility can mean, for instance, that the metadata have been published in a repository, through which people can request their use.
  • Interoperable: The research data have been compiled and documented in ways that follow format requirements (adherence to proper form). The data are intelligible and can be used in other contexts as well. 
  • Re-usable: The research data have a clear licence enabling their use. The data have been described comprehensively and meet the quality criteria of the scientific community. 

The FAIR principles are the ideal

The data can meet only some of the FAIR principles but still be valuable. At the master’s level, you should be aware of these principles even if you may be able to follow them only partially.

Try to follow the FAIR principles as carefully as possible, without letting their seemingly impossible sections discourage you. Particularly in the interoperability section, machine-readability is strongly emphasised in the definitions – but it is simply not yet possible for some types of data. The researcher’s (and student’s) primary responsibility is to focus on collecting data in a way that is as systematic and documented as possible. The Open Science Centre will help you with metadata as well as with storing and publishing related to findability and accessibility.

FAIR principles support conducting good science

The FAIR principles are often mentioned in connection with open science and the opening of data. It is true that the principles make it easier to open data, but that is not their only purpose. The FAIR principles and good data management practices are part of conducting good science. They make data and science better – easier to repeat, verify, analyse and report.   

If you want, you can read more about the FAIR principles and watch a short video on FAIR.