Barriers to Collaboration: Lessons Learned from the Data Curation Network.” Research Library Issues, no. 296 (2018): 37–43.

Data Curation Network: A Cross-Institutional Staffing Model for Curating Research Data. (2018). International Journal of Digital Curation. Vol 13 No 1 (2018).

Abstract: The Data Curation Network (DCN) provides a solution for partners of all sizes to develop or to supplement local curation expertise with the expertise of a resilient, distributed network, and creates a funding stream to both sustain central services and support expansion of distributed expertise over time. This paper presents our next steps for piloting the DCN, scheduled to launch in the spring of 2018 across nine partner institutions. Our implementation plan is based on planning phase research performed from 2016-2017 that monitored the types, disciplines, frequency, and curation needs of data sets passing through the curation services at the six planning phase institutions. Our DCN implementation plan includes a well-coordinated and tiered staffing model, a technology-agnostic submission workflow, standardized curation procedures, and a sustainability approach that will allow the DCN to prevail beyond the grant-supported implementation phase as a curation-as-service model.

(preprint) Data Curation Network: A Cross-Institutional Staffing Model for Curating Research Data. (2017). University of Minnesota Digital Conservancy.

Abstract: Unabridged final report of the Data Curation Network planning phase and includes appendixes: A: Roles and Responsibilities of Key DCN Staff, B: Draft Memorandum of Understanding for Institutional Partners, C: Draft DCN Workflows for DCN Curators, D: Functional Requirements for the DCN Tracking Form.

How Important is Data Curation? Gaps and Opportunities for Academic Libraries. (2018). Journal of Librarianship and Scholarly Communication, 6 (1), eP2198.

Abstract: INTRODUCTION Data curation may be an emerging service for academic libraries, but researchers actively “curate” their data in a number of ways—even if terminology may not always align. Building on past user needs assessments performed via survey and focus groups, the authors sought direct input from researchers on the importance and utilization of specific data curation activities. METHODS Between October 21, 2016, and November 18, 2016, the study team held focus groups with 91 participants at six different academic institutions to determine which data curation activities were most important to researchers, which activities were currently underway for their data, and how satisfied they were with the results. RESULTS Researchers are actively engaged in a variety of data curation activities, and while they considered most data curation activities to be highly important, a majority of the sample reported dissatisfaction with the current state of data curation at their institution. DISCUSSION Our findings demonstrate specific gaps and opportunities for academic libraries to focus their data curation services to more effectively meet researcher needs. CONCLUSION Research libraries stand to benefit their users by emphasizing, investing in, and/or heavily promoting the highly valued services that may not currently be in use by many researchers.

Related Dataset and Interview Protocol:

SPEC Kit #354: Data Curation. (2017). Association of Research Libraries (ARL). May 2017.

Abstract: This SPEC Kit explores the infrastructure that ARL member institutions are using for data curation, which data curation services are offered, who may use them, which disciplines demand services most, library staffing levels, policies and workflows, and the challenges of supporting these activities. It includes examples of data repository web pages, descriptions of services, infrastructure, workflows, metadata schemas, and policies, and job descriptions.
Related dataset:
Webinar on June 14, 2017: 

Data Curation Network: How Do We Compare? A Snapshot of Six Academic Library Institutions’ Data Repository and Curation Services. (2017). Journal of eScience Librarianship 6(1): e1102.

Abstract: Objective: Many academic and research institutions are exploring opportunities to better support researchers in sharing their data. As partners in the Data Curation Network project, our six institutions developed a comparison of the current levels of support provided for researchers to meet their data sharing goals through library-based data repository and curation services. Methods: Each institutional lead provided a written summary of their services based on a previously developed structure, followed by group discussion and refinement of descriptions. Service areas assessed include the repository services for data, technologies used, policies, and staffing in place. Conclusions: Through this process we aim to better define the current levels of support offered by our institutions as a first step toward meeting our project’s overarching goal to develop a shared staffing model for data curation across multiple institutions.

Recent Presentations

  • Presentation (slides) to the DataOne Webinar December 11, 2018
  • Presentation (slides) to the RDAP Fall 2018 Webinar November, 8, 2018
  • Presentation (slides) at DLF Forum Las Vegas, NV October 16, 2018
  • Presentation (slides) at NISO virtual conference “Open Data Projects” June 13, 2018.
  • Presentation (slides) at IASSIST Annual Conference in Montréal, Canada, May 29, 2018 
  • Presentation (slides) at the CNI Spring 2018 Membership Meeting in San Diego, CA on April 12-13, 2018
  • Presentation (slides) at the Research Data Access, and Preservation (RDAP) Summit in Chicago, IL on March 22, 2018 
  • Poster presented at the Research Data Alliance 11th Plenary, Berlin, Germany, March 23, 2018
  • Presentation (slides) presented at the International Digital Curation Conference (IDCC) in Barcelona, Spain February 20, 2018
  • Poster presented at the Community Standards for 3D Data Preservation, St. Louis, MN February 5, 2018

Additional reports and presentations from the Data Curation Network Project Planning Phase (2016-2017) are archived in the University of Minnesota Digital Conservancy at