Carlson, JakeCowles, WindJohnston, Lisa R.Narlock, Mikala R.2022-12-132022-12-132022https://hdl.handle.net/11299/250149In 2016, six academic libraries initiated the Data Curation Network (DCN) as an experimental model for collaboratively curating data sets deposited into their institutional repositories. The DCN model is centered on “radical interdependence”, opening up access to expertise of the data curators at any one institution to all participating member libraries. Under this model, DCN member institutions leverage the collective knowledge and skills of all member curators, creating a greater capacity to curate more data more effectively than any one institution could by themselves. The DCN is now a thriving community and has grown to 17 member institutions. The DCN recently conducted a project retrospective to better understand the enabling structures and tools that allowed the network to thrive. Representatives from the member institutions were recently asked to reflect on their experiences in developing the DCN and what elements contributed to its success. We asked them to consider not just the structures, tools, and workflows that we collectively designed, but the more intangible aspects of the DCN, such as generating trust, acknowledging vulnerability, and community building. In our presentation, we will explore the key enabling structures of “radical interdependence” that were identified by DCN members. We will then lead a discussion on how these structures could potentially be applied to other cross-institutional or multidisciplinary collaborations. Presented at the Coalition for Networked Information Fall 2022 member meeting.enPresentation