At TU Graz, research outputs will be treated according to the FAIR (Findability, Accessibility, Interoperability and Reusability) principles. Adherence to these guidelines enables transparency and reproducibility of research. The principles do not only apply to data, but also to algorithms, tools and workflows leading to the data.

Findability can be ensured by using a unique or persistent identifier with sufficient description of data and their characteristics in machine-readable metadata and storage of data in archives or repositories. 

Accessibility requires that metadata are always available via standardized, universally implementable communication protocols and corresponding datasets have clearly defined access conditions.

Interoperability needs data and metadata kept in common, published standards of data formats, variables or ontologies in order to enable their integration into existing applications or workflows.

Reusability is the ultimate aim of research. Detailed description of characteristics according to community standards with clear conditions enable the reuse of research data for future endeavours.

Implementation of the FAIR principles provides advantages for different stakeholders such as: 

  • researchers, who receive credit for their work and benefit from data shared by other researchers
  • funding agencies aiming for long-term data stewardship
  • professional data publishers getting credit for their software, tools and services for data handling
  • the data science community for exploratory analyses

Have a look at this video on FAIR principles from the Maastricht University

Data organisation broadly refers to keeping research data in such a way as to maximise their findability (by humans). Improved data organisation means imrpoved findability and accessibility to researchs and third parties as well as easier access control with regards to sensitive data.