Even though CLARIN has been in existence for longer than the FAIR data principles themselves, it is clear that the core values of CLARIN – facilitating the reuse of language data and tools for research – align very closely with Findability, Accessibility, Interoperability and Reusability. CLARIN was a FAIR case ‘avant la lettre’.
How CLARIN Enables Data to Be...
- Through the Virtual Collection Registry, enabling publication and sharing of digital bookmarks
- Through the Virtual Language Observatory, a search portal for language data, based on harvested metadata
- Through the (Federated) Content Search, allowing researchers to search multiple corpus search engines at once.
- Through the many CLARIN centres providing a (certified) repository – including support for persistent identifiers
- Though the metadata provided by CLARIN centres
- Through the federated login system, lowering the threshold to login when password-protected access is needed.
- Through the Language Resource Switchboard, providing an easy way to discover which tools can process a language data set
- Through rich vocabularies
- Through explicit and well-documented ways of linking from metadata to (meta)data.
- Through clear recommendations on licenses
- Through clear recommendations on formats and standards
- Through active metadata curation and continuous metadata quality and link checks.
FAIR & CLARIN: The Details
- Jong, Franciska de, Bente Maegaard, Koenraad De Smedt, Darja Fišer & Dieter Van Uytvanck (2018): "CLARIN: Towards FAIR and Responsible Data Science Using Language Resources." In: Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018), May 2018, 3259-3264. (BiBTeX)
- CLARIN and the FAIR principles: presentation (video, 30 minutes)
FAIR & CLARIN: By Example
- Using CLARIN tools to find and analyse cultural heritage data sets (blog article)
- Pairing FAIR with EOSC: finding, accessing and reusing parliamentary speeches (demonstrator)
FAIR & CLARIN: Guidelines
- CLARIN Certified B-centre checklist
- PARTHENOS Guidelines to FAIRify data management and make data reusable (document, 12 pages)