The FAIR data principles are a set of guiding principles to make data Findable, Accessible, Interoperable and Reusable, so that data can be found, understood and reused by others.
There is a need to improve the infrastructure that supports the reuse of scientific data. Stakeholders from the academic world, industry, foundations and scientific publishers have agreed to a set of FAIR data principles, which serve as guidelines for those wanting to improve the ability of their data being reused
When preparing a data management plan, you are complying with the principles of openness and transparency by documenting provenance of the data. By describing who has created the data and metadata, as well as when and under what conditions the data was generated, the data management plan contributes to understanding the data and making research results reproducible. Read more about the benefits of creating data management plans.
A persistent identifier (PID) is a unique key which is used to permanently identify a given document, dataset or person. Often, there are a few descriptive metadata associated with a PID. PIDs allow other people to find and refer to your data. In line with the FAIR principles, PID make data findable and accessible (the "F" and the "A" in the FAIR principles).
Examples of persistent identifiers:
Data licenses are used to show whether your data can be used by others, and how the data can be reused (the "R" in the FAIR principles)
Research data holds considerable value for you, but also for researchers around the world. You can make it easier for others to refer to or use your research data by sharing your data with a clear license. Read more about licenses.
Working with metadata is fundamental when you want to make your research compatible with the FAIR principles. Metadata ensures that your research and research data follow the FAIR principles, even when your data is closed, because the data is confidential, or it contains sensitive personal information etc.
Adding metadata to your datasets ensures that data can be found by both people and machines. Metadata supports the "F", "A", "I" and "R" in the FAIR principles.
Repositories can help you make your data findable, accessible and reusable (the "F", "A" and "R" in the FAIR principles).
They can guide you a much of the way if you want to make your research compatible with the FAIR principles. If you publish your data in an open repository such as Dataverse, Zenodo or Figshare, the principles will, for example, be able to help you:
At AU, we do not have an institutional repository, but there are numerous open repositories which you can use. Often the choice will depend on the subject area, but there are also a number of inter-disciplinary repositories.
There are several resources where you can read, view or hear more about the FAIR principles:
If you have any questions or concerns, feel free to contact the liason librarian associated with your field, who will be happy to assist you with your questions.
Alternatively, you are always welcome to contact your local library.