Authors : Sophia Lafferty-Hess, Julie Rudder, Moira Downey, Susan Ivey, Jennifer Darragh
A growing focus on sharing research data that meet certain standards, such as the FAIR guiding principles, has resulted in libraries increasingly developing and scaling up support for research data.
As libraries consider what new data curation services they would like to provide as part of their repository programs, there are various questions that arise surrounding scalability, resource allocation, requisite expertise, and how to communicate these services to the research community.
Data curation can involve a variety of tasks and activities. Some of these activities can be managed by systems, some require human intervention, and some require highly specialized domain or data type expertise.
At the 2017 Triangle Research Libraries Network Institute, staff from the University of North Carolina at Chapel Hill and Duke University used the 47 data curation activities identified by the Data Curation Network project to create conceptual groupings of data curation activities.
The results of this “thought-exercise” are discussed in this white paper. The purpose of this exercise was to provide more specificity around data curation within our individual contexts as a method to consistently discuss our current service models, identify gaps we would like to fill, and determine what is currently out of scope.
We hope to foster an open and productive discussion throughout the larger academic library community about how we prioritize data curation activities as we face growing demand and limited resources.