28 Association of Research Libraries Research Library Issues 298 — 2019 Building Capacity for Data Science with Help from our Friends Cynthia Parr, Technical Information Specialist, National Agricultural Library, Agricultural Research Service, US Department of Agriculture Susan McCarthy, Associate Director, Knowledge Services Division, National Agricultural Library, Agricultural Research Service, US Department of Agriculture Introduction Among the latest corporate and academic fads is “data science,” that often ambiguously defined collection of data analytics activities that promises to take us all to the next level of efficiency and knowledge. Especially when combined with other buzzwords like “big data” and “open data,” data science appears to be somewhere between the “peak of inflated expectations” and the “trough of disillusionment” in Gartner’s hype cycle.1 One might wonder how, and even why, a research library should dip its toes into these murky waters. At the United States Department of Agriculture (USDA) National Agricultural Library (NAL), we believe that the answer to “why explore data science?” is that institutional experience with core data-science activities will inform the larger set of data and data management services the library performs.2 Moreover, engaging information science students and library managers in data science projects builds capacity both for us and for the communities we serve. The answer to “how?” is “not alone.” In this article, we describe how NAL, in collaboration with the University of Maryland College of Information Studies (UMD iSchool), the USDA Agricultural Research Service (ARS), and university librarians (the “friends” in the title), is using lean start-up methodology to enable us all to continue a long tradition of supporting agricultural knowledge generation, dissemination, and preservation. At NAL, we consider data science to include, but not be limited to, the core analytical activities necessary for deriving insight from data. We recognize that data science activities are practiced not only by