Many field stations and marine laboratories (FSMLs) must rely on ad hoc tools to manage work, making it difficult to track who conducted research, what was produced, and how the station contributed to scientific advancements. Because of this, when datasets, samples, and papers are eventually published, key metadata linking them back to the FSML is often lost, leaving institutions without the robust information we need to track their contributions to the scientific record.
Through our NSF-funded FAIR Island and FAIR Samples projects, UC3 experimented with ways to tackle these challenges. With our new Moore Foundation-funded FAIR Station project, we will be working in partnership with our colleagues at the University of California Natural Reserve System to (re)imagine and extend the capabilities of UC’s existing Reservation Application Management System (RAMS) platform to transform the routine booking of time at an FSML into a strategic opportunity to solve these systemic issues.
What is it?
The FAIR Station initiative is a collaboration to develop a next-generation, open-source reservation and research-tracking platform that connects field-based scientific research activities to their outputs. Our goal is to streamline how fieldwork is tracked and ensure that station activity is visible and discoverable. The purpose is to empower FSML managers, researchers, and communities across the UCNRS and the world to demonstrate the impact of their work and build a more connected, open, and equitable research ecosystem and position FSMLs not just as operational hubs, but as essential contributors to scientific knowledge and environmental stewardship. By embedding persistent identifiers, including IGSNs, ORCIDs, RORs, and DOIs directly into reservation workflows, we ensure that station activity flows naturally into downstream metadata systems.
This approach helps make research outputs more discoverable, reusable, and attributable, while positioning field stations not just as operational sites, but as essential contributors to scientific knowledge and environmental stewardship.
Next Steps
The project will launch in Q2 2026 with the open sourcing of UC’s RAMS system. The relaunched system will be supported by APIs, enabling community-driven enhancements, integrations, and local customization. As the project progresses, we hope to extend functionality to better support the global FSML community:
- Impact tracking via PIDs: This crucial step ensures that station information flows automatically through the metadata of samples collected, datasets published, and papers produced. The result is a queryable, publicly available record that enables institutions to identify research outputs associated with their sites.
- Policy and data management compliance: DMPs, permitting, and required checks can be embedded directly into reservation workflows, helping researchers and stations align early with national, local, Indigenous, and international data policies without adding downstream administrative burden.
- Metadata quality and reuse: Information collected during reservations (such as people, places, projects, permits, and instrumentation) can be reused to populate downstream metadata, reducing duplication and improving consistency across repositories, registries, and reporting systems.
- Long-term stewardship of research outputs: By connecting reservation workflows to trusted repository infrastructure, we can help ensure that datasets and related materials are deposited, preserved, and referenced in ways that align with institutional and community best practices.
- Reporting, assessment, and strategic decision-making for institutions: Aggregated, structured metadata enables stations and institutions better understand research activity over time, support reporting needs, and demonstrate value to funders, administrators, and partner communities.
- Open, extensible platform. Through open APIs and modular design, the next-generation RAMS platform will support local customization, third-party integrations, and shared enhancements developed collaboratively by the FSML community.