Berlin Institute of Health at Charité - Universitätsmedizin Berlin.
Stud Health Technol Inform. 2024 Jan 25;310:154-158. doi: 10.3233/SHTI230946.
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.
医疗保健中的决策在很大程度上依赖于可发现、可访问、可互操作和可重复使用（FAIR）的数据。基因组学的不断发展也在很大程度上依赖于 FAIR 数据，以指导未来可靠的研究。从实际目的出发，确保临床数据集的 FAIR 性可能具有挑战性，但可以通过使用 FAIR 验证器来辅助。本研究描述了在演示版本中对两个开放获取的网络工具进行测试，以确定三个具有不同格式（JSON、TXT、CSV）的提交基因组文件的 FAIR 级别。F-UJI 工具和 FAIR-Checker 工具为三个提交的文件提供了相似的 FAIR 分数。然而，F-UJI 工具给出了总评分，而 FAIR-Checker 则根据 FAIR 原则给出了聚类评分。这两个工具都不适合确定 FHIR® JSON 元数据文件的 FAIR 级别。尽管它们处于早期开发阶段，但 FAIR 验证工具具有很大的潜力，可以帮助临床医生实现他们的研究数据的 FAIR 化。
