FAIR-Checker

FAIR-Checker evaluates and improves the adherence of digital bioinformatics resources to the Findability, Accessibility, Interoperability, and Reusability (FAIR) principles by assessing and enriching machine-actionable metadata.

Key Features:

• Check module: Evaluates metadata against the FAIR principles and produces detailed assessments and recommendations.
• Inspect module: Assists in refining metadata to improve the FAIRness of digital resources.
• Semantic Web technologies: Applies SPARQL queries and SHACL constraints to automate metadata validation and checks.
• Metadata notifications: Detects and reports missing, necessary, or recommended metadata specific to resource categories.
• Machine-actionable metadata support: Facilitates the creation and enrichment of rich, machine-actionable metadata for datasets, bioinformatics tools, and training materials.
• Large-scale evaluation: Has been applied to assess the FAIRness of over 25,000 bioinformatics software descriptions.

Scientific Applications:

• Metadata FAIRness assessment: Evaluates and benchmarks metadata quality for datasets, bioinformatics tools, and training materials.
• FAIRification guidance: Informs targeted metadata improvements to enhance Findability, Accessibility, Interoperability, and Reusability.
• Large-scale metadata analysis: Enables population-level analysis of bioinformatics software descriptions and metadata quality.

Methodology:

Automated assessment using Semantic Web technologies, specifically SPARQL queries and SHACL constraints, with detection and notification of missing, necessary, or recommended metadata per resource category.