Published June 4, 2025 | Version v1
Poster Open

Developing Collaborative Data Services and Instruction

  • 1. ROR icon Cornell University

Contributors

  • 1. ROR icon Cornell University

Description

Research Data and Open Scholarship is a centralized library service at Cornell University dedicated to facilitating ethical stewardship and sharing of research and scholarship. While the formation of this group is relatively new, librarians at Cornell have been providing 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 made it easier for researchers to produce FAIR data (findable, accessible, interoperable, and reusable) and significantly contributed to increased research reproducibility and collaboration across disciplines. In the current research landscape, with increased awareness and adoption of data sharing and open scholarship practices, the need for instruction and support around good data management practices in all fields of study are crucial.  

This coming academic year (25/26AY), we plan to hold a series of skill-based workshops focused on data and coding tools that align with the various stages of the research data lifecycle. Our goals for the workshop series include integrating open science practices such as reproducibility and transparency; providing instruction in data and computational skills that are broadly applicable across disciplines and skill levels; and building partnerships that foster collaboration and knowledge sharing across the institution. 

In this poster, we will discuss our approach to inclusive instructional design that supports different learning styles, our collaborations within the library and across campus, our strategies for marketing and outreach, and our methods for assessment and continuous improvement. We will also reflect on challenges we have encountered, such as navigating a large and complex library system with overlapping data service areas. 

Files

DevelopingCollaborativeDataInstructionCornell_EvergreenMcKee_2025.pdf

Files (455.9 kB)