Shifting to Data Savvy: The Future of Data Science In Libraries

Abstract

The Data Science in Libraries Project is funded by the Institute for Museum and Library Services (IMLS) and led by Matt Burton and Liz Lyon, School of Computing & Information, University of Pittsburgh; Chris Erdmann, North Carolina State University; and Bonnie Tijerina, Data & Society. The project explores the challenges associated with implementing data science within diverse library environments by examining two specific perspectives framed as ‘the skills gap,’ i.e. where librarians are perceived to lack the technical skills to be effective in a data-rich research environment; and ‘the management gap,’ i.e. the ability of library managers to understand and value the benefits of in-house data science skills and to provide organizational and managerial support.

This report primarily presents a synthesis of the discussions, findings, and reflections from an international, two-day workshop held in May 2017 in Pittsburgh, where community members participated in a program with speakers, group discussions, and activities to drill down into the challenges of successfully implementing data science in libraries. Participants came from funding organizations, academic and public libraries, nonprofits, and commercial organizations with most of the discussions focusing on academic libraries and library schools.