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Our Path to FAIR Station

John Chodacki,

Posted in: FAIR Station, UC3

At UC3, our work focuses on how research activities, outputs, and systems connect across the lifecycle, from planning and data collection through to publication and reuse. We approach these challenges from a research infrastructure and information management perspective, which naturally extends upstream to where research begins, including field stations and other place-based environments. As we embark on the FAIR Station project, we wanted to reflect on some of the many projects and work that got us to this point.

Early foundations

UC3 was founded as CDL’s digital curation program to focus on supporting the full research lifecycle. For more than 15 years, our work has centered on enabling connections from planning and data collection. One of our most formative collaborations was with the DataONE community. That vision was ambitious: to support discovery, access, and reuse of environmental data across a distributed landscape, grounded in the realities of field-based, place-dependent research.

DataONE’s emphasis on lifecycle coordination and distributed data collection reinforced the importance of capturing context at the point of origin. These ideas, grounded in foundational work by UC3 and supported through NSF investment, continue to inform our work. At the same time, UC3’s other collaborations explored various entry points into the research lifecycle. 

As a founding member of the DataCite community, we helped lead the adoption of DOIs for research data, strengthening how outputs are identified and connected. The DMPTool supports planning and structuring, while repository services enable publication and citation. In parallel, early work on field station identifiers, including pilots and community presentations, surfaced the importance of treating place as a first-class entity rather than background context. 

Engagement with communities such as RDA, ESIP and OBFS further highlighted the challenges of connecting data, samples, and locations across distributed systems. This work established a strong foundation, but also exposed a critical gap: research context is not consistently captured or linked across the lifecycle.

Making infrastructure actionable

Over the past 10 years, a series of funded projects and community initiatives focused on strengthening the connective tissue of the research ecosystem. This included:

During this period, UC3 also contributed to building shared identifier infrastructure, including the Research Organization Registry (ROR) (NSF EAGER, 2020) and broader PID strategy efforts. This work built directly on earlier exploration with the OBFS and NAML on field station identifiers, where efforts to identify place-based environments shaped our thinking about organizational identity, disambiguation, and persistent identifiers. This work established the ability to link research entities, while also making clear that identifiers alone are not sufficient without being embedded into real workflows.

During this same time, UC3 also worked closely with Dryad to evolve it into a platform for experimentation: collaborating on affiliation tracking, linking datasets to software and publications, and early integrations with data management planning workflows. These efforts moved infrastructure into practice, but also highlighted a limitation: much of our work remained downstream. The question of how to integrate these capabilities into place-based research environments remained.

FAIR Island: Infrastructure, Policy, and Practice

Over the years, UC3 has seen increasing alignment across our work in data management planning, persistent identifiers, and research outputs, and recognized an opportunity to bring these together in a place-based context. Through a partnership with UCNRS, and in particular with our frequent collaborators at the Gump South Pacific Research Station, we identified the field station reservation process as a strategic point of engagement where these elements could be introduced earlier in the research lifecycle.

UC3 made the case internally to pursue this work, leading to initial UC investment in what became the FAIR Island project. The core idea was to take the data policies and expectations typically expressed in grant applications and DMPs, and embed them directly into field station workflows. By working to integrate the DMP Tool with the UCNRS Reservation Application Management System (RAMS), we began exploring how policy, identifiers, and metadata could be introduced at the point where researchers request access to field sites.

This work marked the beginning of a deeper collaboration across UCOP, bringing together research infrastructure and operational systems that support day-to-day field station activities. With subsequent NSF support, FAIR Island expanded to include additional partners, including Metadata Game Changers and the Tetiaroa Society, allowing us to test more complete, end-to-end workflows across planning, data collection, and downstream integration.

Our work on FAIR Island demonstrated the importance of the reservation process. It represents a moment where researchers are already providing structured information, making it a natural and effective place to introduce data policies, identifiers, and expectations that can carry forward through the rest of the research lifecycle. This began a shift from connecting data after the fact to embedding those connections where research begins.

FAIR Samples and vertical interoperability

Building on this foundation, our recent projects have expanded into data collection workflows and cross-system integration. The FAIR Samples project (NSF EAGER, 2024) focuses on improving how physical samples are identified, described, and connected across workflows. A key focus is integrating sample management systems with the broader research ecosystem. This work builds on the concept of vertical interoperability, developed by our partners at RSpace, which focuses on how information moves across layers of the research process, from planning tools and field data collection to lab systems and repositories.

Rather than introducing new systems, the FAIR Samples approach emphasizes connecting existing infrastructure, including IGSNs for samples, tools like FieldMark for structured field data capture, and platforms like RSpace for managing and linking workflows. Together, these integrations demonstrate how coordinated tools can support end-to-end workflows without requiring entirely new systems. 

FAIR Station: Bringing it all together 

This brings us to FAIR Station. This project is not a new direction, but a continuation of our broader efforts to connect place, samples, and data across the research lifecycle. 

Collaboration with UCNRS and work with its RAMS platform has been central to our efforts. What began as an operational system that was not easily extended has, through sustained UC investment, evolved into a platform that is now much better positioned for integration. That shift creates a new phase of opportunity for UC3 and UCNRS to work together on connecting planning, policy, identifiers, and downstream systems in ways that were not previously feasible.

It also opens the door to thinking beyond UC. As RAMS continues to mature, we began exploring how it can be extended and open sourced, creating a foundation that other field stations and research networks can adopt, adapt, and contribute to. The goal is not just to support a single system, but to help enable a broader platform where the global field station community can see themselves and participate. With funding from the Moore Foundation, we can now bring together this work and these partnerships to explore how field station systems can support more connected, interoperable research workflows at scale.

Looking ahead

Across UC3’s projects, there is a consistent way of working: connecting existing efforts, aligning with community practices, and building on infrastructure already in use rather than creating new systems in isolation. All of UC3’s work has only been possible through sustained support from funders and collaboration with communities and partners. That same model is essential for FAIR Station. We will continue to work with field stations, infrastructure providers, and partners like RSpace to extend systems like RAMS and support open, interoperable workflows.