Supporting curators as core infrastructure for data sharing: Lessons from a national survey of Canadian repository

This study examined how Canadian institutions support the administration and curation of research data within repository services, with the goal of understanding the human and organizational conditions needed to advance open science. As data sharing requirements from funders and publishers expand, understanding how institutions support data deposit, curation, and long‑term stewardship is essential for sustaining open science. The study aimed to assess institutional readiness, characterize service models, identify challenges faced by research data repository administrators, and evaluate the perceived value of a national community supporting this shared infrastructure. A national survey was sent to all Canadian institutions operating Dataverse collections as part of the emerging national shared infrastructure or separate institution-managed installations. Forty‑six institutions completed the survey, representing a majority of the population at the time of data collection. Institutions reported substantial variation in staffing and service maturity, with many small institutional participants facing acute capacity limitations. Most institutional participants allocated minimal staff time to repository administration, yet the majority expected deposit rates to increase in the near term. Larger participating institutions were more likely to report robust and well‑established services, while smaller participating institutions frequently described their services as emerging or still under development. Across institution sizes, administrators identified researcher awareness, limited incentives for data deposit, and insufficient staffing as major challenges. While many participating institutions conducted basic dataset review activities, advanced curation services were less common, particularly among smaller institutions. Respondents emphasized the value of participating in a national community of practice, which provides shared expertise, collective problem‑solving, and a foundation for strengthening open science capacity across diverse institutional contexts. These findings underscore that open science relies fundamentally on human expertise: sustaining high‑quality, equitable, and trustworthy data sharing requires dedicated investment in the people and processes that make open data possible.