M4.2: FAIRagro Federated RDI Network: Consolidation of Research Metadata
Abstract
The FAIRagro Federated RDI Network integrates metadata from heterogeneous research data infrastructures (RDIs) into a unified framework. It addresses the challenges of diverse technologies, inconsistent metadata models, and missing APIs. In 2025, the key contribution is the SQL-to-ARC approach, enabling standardized generation of Annotated Research Contexts (ARCs) and their consolidation within the network. The introduction of the ARC concept itself was first proposed by Jorge García Brizuela et al., while the SQL-to-ARC approach is a subsequent development.
Full text
Concept/Roadmap FAIRagroDataHub M4.2: FAIRagro Federated RDI Network: Consolidation of Research Metadata “The middleware” The FAIRagro Federated RDI Network integrates metadata from heterogeneous research data infrastructures (RDIs) into a unified framework. It addresses the challenges of diverse technologies, inconsistent metadata models, and missing APIs. In 2025, the key contribution is the SQL-to-ARC approach, enabling standardized generation of Annotated Research Contexts (ARCs) and their consolidation within the network. The introduction of the ARC concept itself was first proposed by Jorge García Brizuela et al. [1], while the SQL-to-ARC approach is a subsequent development. RDIs RDIs RDIs API sitemap Middleware Pull metadata Discovery & Harvest service Push JSON-LD dumps 1 Jorge García Brizuela 1, Carsten Scharfenberg 2, Xenia Specka 2, Matthias Lange 1, Daniel Arend 1 1 - Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Germany 2 - Leibniz Centre for Agricultural Landscape Research (ZALF) Müncheberg, Germany 3 scan me This work was created as part of the NFDI consortium FAIRagro (www.fairagro.net). We gratefully acknowledge the financial support of the German Research Foundation (DFG) – project number 501899475 ARC Concept Developed by NFDI4Plants, ARC (for Annotated Research Context) is a FAIR-compliant object that connects data, workflows, and ontology-based annotations to support transparent, reproducible, and interoperable research across the entire data lifecycle. ARCs are stored in the DataHub, a customized GitLab instance. SQL DATABASE RDIs SQL-to-ARC Client standardized database views RO-Crate JSON store ARCs Advance Middleware alternative Client build enrich/harmonize ontology references curate Datahub GitLab FAIRagro ontology Advance Middleware - ARC Rest API domain experts proprietary access Middleware API (2025) AgriSchema (2027) Alternative client (on demand) SQL-to-ARC client (2025) schema.org (2024) ontology reference enchrichment/harmonization INSPIRE/DCAT-AP (2027) Harvester (2024-2027) pull push SearchHub SciWIn Use Cases RDIs Datahub / gitlab (2025) 12 3 DataHub DataHub DataHub Federated RDI Uses standard Schema.org metadata → easy to collect & share. Simple setup with a test instance for users Schema.org by itself does not provide sufficient coverage for comprehensive metadata and semantic information, leaving the community without a unified standard. The SQL-to-ARC approach helps fill this gap by enabling RDIs to define standardized SQL views, which the SQL-to-ARC tool then transforms into ARCs in the RO-Crate JSON-LD format. These ARCs are ingested by the Middleware API and stored as Git repositories in the Datahub. While RDIs may adopt SQL-to-ARC, it is optional—custom client software can also connect directly to the Middleware API. Recent Developments [1] Journal of Integrative Bioinformatics 2024-11-27 | Journal article DOI: 10.1515/jib-2024-0027 Authors: Jorge García Brizuela; Carsten Scharfenberg; Carmen Scheuner; Florian Hoedt; Patrick König; Angela Kranz; Antonia Leidel; Daniel Martini; Gabriel Schneider; Julian Schneider et al. 2