Geodetic Data: Applying FAIR, TRUST and CARE Principles

Geodetic research fundamentally relies on observational data, long-term monitoring, and operational infrastructures spanning decades and national boundaries. In this context, data are not merely by-products of research but essential scientific assets. The principles summarized by the acronyms FAIR, TRUST, and CARE provide a coherent framework for ensuring that geodetic data remain usable, reliable, and shared responsibly in the long term.

FAIR Principles for Research and Operational Data

The FAIR Principles for Research Data Management were first described by Wilkinson et al. (2016). FAIR stands for “Findable, Accessible, Interoperable and Reusable”, thereby providing a concise definition of how research data should be handled. In summary, the principles aim to improve the sharing and reuse of data to enable the reproducibility of research results, as well as the processing and reinterpretation of data by humans and machines. Data should be 

• findable through persistent identifiers (e.g., DOIs, ORCIDs for authors, ROR for institutions and funders) and rich descriptive metadata,
• accessible via well-defined protocols,
• interoperable through the use of community standards (e.g., commonly used reference systems, standard data formats, etc.), and
• reusable through clear documentation, provenance, and licensing. In geodesy, many of these elements are already familiar through internationally standardized formats, reference frames, and service-based data provision.

However, FAIR implementation requires these practices to be made explicit, consistent, and machine-readable across all data types, services and associated metadata.

TRUST Principles for Digital Repositories

TRUST (Transparency, Responsibility, User focus, Sustainability, Technology, Lin et al., 2020) complements FAIR by focusing on the “trustworthiness” of digital data repositories and institutions that curate (geodetic) data. While the FAIR principles focus on the qualities of the data itself, the TRUST principles focus on the systems and organizations responsible for preserving it safely over time. Trustworthy data repositories are transparent, clearly define responsibilities for data stewardship, processing and long-term maintenance and access of data products. For geodetic data, which often form the basis for international reference systems and global monitoring activities, institutional continuity, sustainable funding, and robust technical infrastructure are essential. TRUST ensures that data published and cited today can still be accessed, understood, and reproduced many years into the future.

CARE for Responsible and Ethical Data Use

CARE (Collective Benefit, Authority to Control, Responsibility, Ethics) addresses the ethical and societal dimensions of data collection, governance and sharing. While geodetic data are often perceived as purely technical, geodetic infrastructures and observations are embedded in societal, cultural, and political contexts. Originally developed in the context of Indigenous Data Governance, the CARE principles emphasize collective benefit, appropriate authority over data, responsibility, and ethical use. Applied to geodesy, this means providing adequate context, limitations, and uncertainty information, while also considering the perspectives of potentially affected communities, sensitive infrastructures, and local contexts. CARE reminds the scientific community that openness and data sharing should not come at the expense of ethical responsibility and respect for legitimate societal interests. The FAIR principles explain how to make data technically shareable and reusable, while the CARE principles explain whether and under what conditions data sharing is appropriate and ethically responsible. In modern data science, repositories and research infrastructures are increasingly encouraged to ”be FAIR and CARE”.

Applying FAIR, TRUST and CARE through DOI Implementation

The importance of FAIR, TRUST, and CARE becomes particularly evident when it comes to the persistent identification and citation of geodetic data. The GGOS Committee on Digital Object Identifiers (DOIs) for Geodetic Data Sets was established to address these challenges precisely. By promoting consistent DOI usage across IAG Services, the Committee strengthens the FAIR principles, making geodetic data findable, citable, and traceable. It also reinforces TRUST through standardized citation practices and long-term commitments of the selected digital data repositories. Assigning DOIs to geodetic data products gives data providers and institutions scientific recognition and enables the use quantitative metrics to demonstrate the value of sustained observational efforts.

This approach is supported by the GGOS DOI Committee’s “Metadata Recommendations for Geodetic data: GNSS”  (https://doi.org/10.5281/zenodo.16992828). The document translates the FAIR principles into practical guidance by connecting DOI metadata standards, such as DataCite and ISO 19115, with community-specific metadata standards such as GeodesyML and station logs. Although it was developed for GNSS data, many of its recommendations can be applied to other geodetic techniques and data products.

Summary and Outlook

Together, the principles of FAIR, TRUST, and CARE provide a shared conceptual foundation for geodetic data management. Initiatives such as the GGOS DOI Committee demonstrate how these principles can be implemented in practice. For geodesy, adopting this framework is not just an administrative exercise but a prerequisite for ensuring the long-term scientific value of geodetic data and services, international interoperability under ethical conditions, and sustained trust in these data and services.

Authors: Kirsten Elger (Chair of GGOS Committee on DOI), Martin Sehnal (Director of GGOS CO)

 

References/ Read more:

• GGOS DOI Committee, et al. (2025). Metadata Recommendations for Geodetic data: GNSS. Zenodo. https://doi.org/10.5281/zenodo.16992828
• Wilkinson et al. (2016). The FAIR Guiding Principles for scientific data management and stewardship. Scientific Data, 3(1). https://doi.org/10.1038/sdata.2016.18
• Lin et al. (2020). The TRUST Principles for digital repositories. Scientific Data, 7(1). https://doi.org/10.1038/s41597-020-0486-7
• Carroll et al. (2020). The CARE Principles for Indigenous Data Governance. Data Science Journal, 19. https://doi.org/10.5334/dsj-2020-043
• Carroll et al. (2021). Operationalizing the CARE and FAIR Principles for Indigenous data futures. Scientific Data, 8(1). https://doi.org/10.1038/s41597-021-00892-0
• RDA International Indigenous Data Sovereignty IG (2019). CARE Principles for Indigenous Data Governance. https://www.rd-alliance.org/wp-content/uploads/2024/03/CARE20Principles20for20Indigenous20Data20Governance_OnePagers_FINAL20Sept2006202019.pdf