Developing Collaborative Data Services and Instruction

Research Data and Open Scholarship is a centralized library service at Cornell University that is charged with facilitating ethical stewardship and sharing of research and scholarship. While the formation of this group is relatively new, librarians at Cornell have been providing and developing data services to the research community for over 15 years. What began as basic data management planning has transformed into comprehensive services that encompass not only data planning and storage, but also sharing, long-term preservation, and the widespread adoption of persistent identifiers like ORCIDs and DOIs. These advancements have not only facilitated the creation of FAIR data (findable, accessible, interoperable, and reusable) but have also played a crucial role in enhancing research reproducibility and collaboration across disciplines. In the current research landscape, with increased awareness and adoption of data sharing and open scholarship practices, monitoring and responding to data management needs is more important than ever. Providing data management services not only helps researchers comply with funding agency and publisher requirements but also enhances the reproducibility and impact of their research. While we continue to support the scientific community, we also seek to extend our reach to non-scientific research communities. As data sharing mandates become more common in other fields (i.e. the new NEH Public Access Policy), the need for instruction and support around good data management practices in all fields of study are crucial. We are exploring ways to broaden our reach and develop targeted services for researchers in the interpretive social sciences and humanities, as well as early scholars who are producing nontraditional research outputs, and researchers who may not consider themselves as working with “data.” Our outreach and instruction plan will require building partnerships with research and learning services librarians across the university, and perhaps changing the way we talk and teach about data.