Assessing the FAIRness of Software Repositories Using RDF and SHACL

EasyChair Preprint 13854, version 1

Abstract

Purpose: A previous paper proposed the usage of SHACL to assess the FAIRness of software repositories. Following this call to action, this paper introduces and discusses the changes made to QUARE, a SHACL-based tool for validating GitHub repositories against sets of quality criteria, to facilitate this task.
Methodology: An operationalization of the abstract FAIR best practices from previous work is devised to enable a FAIRness assessment based on concrete quality criteria. Afterwards, a SHACL shapes graph implementing these constraints is introduced, followed by a discussion of the efficient generation of suitable RDF representations for GitHub repositories. Improvements regarding the usability of QUARE are examined, as well. An evaluation on the FAIRness of 223 GitHub repositories and on the runtime performance of the assessment is conducted.
Findings: On average, trending repositories comply with fewer FAIR best practices than repositories expected to be FAIR. However, the latter still exhibit deficiencies, for example, regarding the correct application of semantic versioning. The low av erage runtime of the FAIRness assessment of respectively 3.50 and 5.73 seconds per repository permits the integration of QUARE in, e.g., CI/CD pipelines.
Value: The FAIR principles are often mentioned as a measure to tackle the reproducibility crisis, which continues to have a significant impact on science. To implement these principles in practice, it is crucial to provide tools that facilitate the automated assessment of the FAIRness of software repositories. The enhanced version of QUARE introduced in this paper represents our proposal for this demand.

Keyphrases: FAIR software, GitHub repositories, SHACL

@booklet{EasyChair:13854,
  author    = {Tobias Hummel and Leon Martin and Andreas Henrich},
  title     = {Assessing the FAIRness of Software Repositories Using RDF and SHACL},
  howpublished = {EasyChair Preprint 13854},
  year      = {EasyChair, 2024}}