FAIR data: as open as possible, as closed as necessary

It is becoming increasingly important for researchers to make their data, code, software and other research outputs accessible to all. While this practice, known as ‘open science’, is a powerful driver for transparency and accountability in scientific research and increased collaboration, some researchers have legitimate concerns about the protection of sensitive data (such as privacy, security or commercial interests), and the risk of their openly published research being scooped by others. Some researchers also question how their research information can be organised effectively to make it not just openly available, but also easily found, understood, exchanged and cited.

FAIR data principles

Image: https://book.fosteropenscience.eu

It is for this reason that institutions such as UCT, in line with many major funding bodies, support the principles of FAIR data – research information that is as open as possible, and as closed as necessary.

According to the FAIR principles, data should be:

  • Findable: ensuring that your data can be found by both humans and machines, by using a globally unique and persistent identifier (such as a DOI, kind of like an ORCID for data) and standardised, machine-readable metadata.
  • Accessible: once someone has found your data, they need to know how they can get access to them. This could include going through an authorisation and/or authentication process – i.e. it does not have to be open access to be FAIR (ethics always trump openness).
  • Interoperable: the use of open formats ensures that your data can be integrated with other data and that they can be utilised by many applications or workflows for analysis, storage, and processing into the future, regardless of changes in software.
  • Reusable: ensuring that your data (and their related metadata) are openly licensed and well-described, indicating unambiguously how they may be reused without a need to contact the author(s) first.

Even if you cannot make your data completely open access, practising good research data management helps you make your research more efficient.

UCT supports several systems to facilitate FAIR publication. These include:

  • UCT DMP, an online platform that assists with the preparation of a data management plan. It offers various DMP templates that meet the requirements of different funding bodies and institutions, and includes detailed information on formulating your plan.
  • ZivaHub, UCTs institutional data repository (powered by Figshare for institutions) for the uploading of supplementary research data that inform scholarly outputs, such as journal articles and theses, hosted on OpenUCT and elsewhere.

UCT is also in the final phase of the Research Data Integration Project, an initiative that streamlines UCT’s various systems and processes, and makes FAIR data publishing easier for researchers.

There are many resources available to the UCT research community to help navigate the complexities of research data management. The teams at UCT eResearch and Digital Library Services offer a range of training, workshops and seminars, while a community of data stewards and champions at UCT advocate and implement the best practices around scholarly data.

For more information and assistance, contact Digital Library Services at dls@uct.ac.za.

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