Implementation and Assessment of An End-to-end Open Science & Data Collaborations Program

Background: There is an increasing need to share data and other research products in accordance with open science principles. Open science not only helps satisfy funder and publisher mandates and accelerate the dissemination of research, but importantly, facilitates collaboration and makes research more reproducible and reusable. Many academic institutions have established institutional repositories (IR) and open-access programs to support open data and publishing. However, these initiatives often emphasize the end product of research. At [an R1 institution], we implemented the Open Science & Data Collaborations (OSDC) program, within University Libraries, that helps embed open science practices into the entire research lifecycle.

Description: The OSDC program was created in 2018 by subject and data librarians and specialists, many with deep research backgrounds in various disciplines. The implementation had 3 phases: the foundation phase that focused on launching essential services, the expansion phase that added more services and generated buy-in and partnerships on campus, and the current assessment phase, in which we plan to use data-driven approaches to further extend services and evaluate impact. The program has 5 pillars: 1) Tools that facilitate collaboration and sharing of research data, code, protocols, and more; 2) Training opportunities that build basic data science competency essential for producing transparent and reproducible research; 3) Events to connect research communities and promote a cultural shift; 4) Collaboration opportunities for researchers to work on data projects together; 5) Assessment that evaluates the impact of open science on research.

Conclusion: The OSDC program supports numerous researchers and has strong partnerships on campus. It is among the first end-to-end open science programs in North America, and is uniquely led by the Libraries, allowing for interdisciplinarity and synergy with related services such as open data and publishing and research data management. We are working on developing metrics to evaluate the program’s impact. As proof of concept, we collected data that includes platform usage, event / workshop registrations, and outreach efforts. Based on initial analysis of this dataset, we developed a metrics framework for future program assessment. This framework, together with a logic model, will guide us to develop targeted surveys and identify priority service areas. Our program can serve as a model for other universities implementing open science initiatives, and we welcome partnerships to form an alliance of open science programs.