How to Assess FAIRness of Your Data - A Summary of Testing Two FAIR Validators.
Stud Health Technol Inform
; 310: 154-158, 2024 Jan 25.
Article
en En
| MEDLINE
| ID: mdl-38269784
ABSTRACT
Decision-making in healthcare is heavily reliant on data that is findable, accessible, interoperable and reusable (FAIR). Evolving advancements in genomics also heavily rely on FAIR data to steer reliable research for the future. For practical purposes, ensuring FAIRness of a clinical data set can be challenging but could be aided by using FAIR validators. The study describes the test of two open-access web-tools in their demo versions to determine the FAIR levels of three submitted genomic data files with different formats (JSON, TXT, CSV). The F-UJI tool and FAIR-Checker tools provided similar FAIR scores for the three submitted files. However, the F-UJI tool assigned a total rating whereas the FAIR-Checker gave scores clustered by FAIR principles. Neither tool was suited to determine FAIR levels of a FHIR® JSON metadata file. Despite their early developmental status, FAIR validator tools have great potential to assist clinicians in the FAIRification of their research data.
Palabras clave
Texto completo:
1
Base de datos:
MEDLINE
Asunto principal:
Genómica
/
Instituciones de Salud
Tipo de estudio:
Prognostic_studies
Idioma:
En
Revista:
Stud Health Technol Inform
Asunto de la revista:
INFORMATICA MEDICA
/
PESQUISA EM SERVICOS DE SAUDE
Año:
2024
Tipo del documento:
Article