Enhanced Radar System, Radar4chem, Boosts Fairness Metrics
In the realm of chemical research data management, the RADAR4Chem project has made significant strides in ensuring its datasets comply with the FAIR (Findable, Accessible, Interoperable, and Reusable) principles. This is achieved through the use of the F-UJI (FAIRness-UJI) score, a metric designed to evaluate the degree of FAIRness in research datasets.
The F-UJI score, a web service that assesses the FAIRness of research data objects at the dataset level, has been instrumental in guiding the evaluation and improvement of RADAR4Chem's dataset FAIRness. By applying the F-UJI score, RADAR4Chem can benchmark the FAIR compliance of its datasets, ensuring they are not only properly documented and accessible but also structured in a way that promotes interoperability and reuse by the broader scientific community.
RADAR4Chem's integration of diverse chemical data and metadata is aided by the F-UJI score, which helps identify gaps in findability or accessibility, evaluate interoperability aspects, and assess reusability. For instance, missing metadata or poor indexing can lead to lower findability scores, while a lack of linking to related resources, such as DOI of a scientific article, can impact the reusability score.
By focusing on these areas, RADAR4Chem has managed to achieve a high level of FAIRness. For the "Interoperable" and "Reusable" criteria, the FAIR level "moderate" was achieved for the majority of RADAR4Chem datasets. The highest FAIR level "advanced" was achieved for the individual criteria "Findable" and "Accessible".
FIZ Karlsruhe, the organisation behind RADAR4Chem, builds a RADAR4Chem knowledge graph daily based on Schema.org vocabulary. This knowledge graph is accessible through a SPARQL endpoint (https://www.radar-service.eu/sparql), allowing for automatic exploration of the RADAR4Chem data in a standardized way. The RDF triples of all RADAR4Chem datasets are also available in turtle format (.ttl) from a specific URL (https://radar4chem.radar-service.eu/knowledgegraph).
In a bid to further improve the FAIRness of its datasets, FIZ Karlsruhe is considering integrating a "FAIRness check" with recommendations for data providers during metadata annotation. This step aims to ensure that the high FAIRness standards are maintained and further improved in the future.
The optimizations made during the support measure have also resulted in an increase in the F-UJI score, with values of up to 87%. This demonstrates the effectiveness of the F-UJI score in driving improvements in FAIRness and the importance of detailed metadata annotation using persistent identifiers.
RADAR4Chem's participation in the FAIRness assessment challenge for datasets and semantic artefacts of the EU project FAIR-IMPACT further underscores its commitment to upholding FAIR principles and continuously striving for improvement.
The F-UJI score, as a web service that evaluates the FAIRness of research data objects, has significantly contributed to RADAR4Chem's improvement of dataset FAIRness by benchmarking compliance, promoting interoperability, and enhancing reusability in data-and-cloud-computing. The integration of the F-UJI score allows RADAR4Chem to identify gaps in findability and accessibility, evaluate interoperability aspects, and assess reusability, ensuring the project maintains a high level of FAIRness, particularly in the areas of Findable, Accessible, and Reusable principles.
