Transforming GNSS Data into FAIR Digital Objects

GNSS (Global Navigation Satellite System) data play a crucial role in both scientific research and practical applications. GNSS datasets are used to monitor atmospheric conditions, tectonic plate movements, and Earth deformation, providing valuable insights for geodetic and geophysical studies. Although widely accessible, GNSS data often lacks the necessary structure and metadata for effective reuse, particularly for data-driven research based on machine learning. To address these challenges, we applied the FAIR (Findable, Accessible, Interoperable, Reusable) data principles to GNSS RINEX observation files hosted by the EUREF Historical Data Centre (EUREF-HDC).

The EU action plan “Turning FAIR into Reality” introduced the concept of FAIR Digital Objects (FDOs), emphasizing the need for Persistent Identifiers (PIDs) and rich, standardized metadata to ensure data can be reliably found, accessed, utilized, and cited. Building on this foundation, we developed a multi-layered FDO structure centered on GNSS RINEX data. Given the established nature of the EUREF-HDC repository, we adapted the FDO concept by prioritizing structured metadata, followed by persistent identifiers and robust (meta)data access procedures.

To implement this approach, we designed the GNSS-DCAT-AP metadata schema, assigned PIDs to both data and metadata, and developed web services enabling humans and machines alike to seamless search, retrieve, and download (meta)data. The effectiveness of our solution was evaluated using the FAIRsFAIR Data Object Assessment Metrics, demonstrating a significant improvement in FAIR compliance.

This work showcases the feasibility of transforming GNSS RINEX data into FAIR Digital Objects and could provide a practical roadmap for other geospatial data repositories seeking alignment with FAIR principles.