2026-10-27 –, LUMC03
What happens to research context when data gets published? Too often, the rich metadata from active research—protocols, collaborators, instruments, but also funding —gets "lost in translation" between lab notebooks and data repositories. Research Activity Identifiers (RAiDs) offer a way to keep that connection alive.
This session presents learnings from the US RAiD pilot program, bringing together two complementary perspectives: ResearchSpace, developers of the RSpace research data management platform, and the University of Texas at Austin's Texas Data Repository. Together, they explore how RAiD can thread through the research lifecycle—from active research documentation to data publication—creating durable, machine-readable connections in the PID graph.
You'll hear about integration patterns, metadata strategies for bi-directional linking, and practical approaches that minimize researcher burden while maximizing the metadata value of your repository deposits.
Do you know where your research data came from—really? Not just the DOI, but the full context: who ran the experiments, which protocols were followed, how the funding connected to the work? For most published datasets, that context is either buried in free-text descriptions or simply lost. RAiD—the Research Activity Identifier—is designed to fix this, by giving research activities themselves a place in a persistent, resolvable identifier.
But what does RAiD integration actually look like in practice? This session gives you a ground-level view from two US RAiD pilot participants who have approached the challenge from two directions.
From the lab notebook side, RSpace introduces RAiDs into active research workflows. When a researcher is documenting experiments, managing samples, and collaborating with their team, RSpace connects these activities to an existing RAiD. When datasets are published—whether to Dataverse, Zenodo, or another repository—RSpace automates reporting back to the RAiD record, keeping the metadata loop closed without requiring researchers to do it manually.
From the institutional repository side, the University of Texas at Austin's Texas Data Repository has been exploring how incoming RAiD references can be incorporated into Dataverse metadata and DOI records. This includes strategies for bi-directional linking: ensuring datasets reference the RAiDs they belong to, and that those RAiD records are updated to reflect new deposits.
Together, these two perspectives show how a connected PID graph can be facilitated in practice.
You'll leave this session with:
- Inspiration for how RAiD can fit into your existing PID ecosystem
- Practical integration patterns for linking active research platforms and institutional repositories through RAiD
- Realistic expectations about researcher burden, implementation complexity, and what you can achieve at different stages of RAiD adoption
Whether you're managing an institutional repository, building research tooling, or advising on research data infrastructure, you'll come away with concrete ideas for where RAiD can add value in your context—and what the first steps toward integration might look like.
