Introduction

The University of California, Los Angeles (UCLA) Library Data Science Center (DSC) is a research and education unit supporting faculty, researchers and students through consultation, instruction, co-curricular programming and data infrastructure. It provides a wide range of researcher support and development in data and computationally intensive scholarship, geospatial analysis and emerging technologies. Since 2018, the DSC has developed services that provide education and support for the increasingly complex research landscape.

This chapter outlines the process used to create the new services. It gives context to the Center's origins as the Social Science Data Archive (SSDA) that provided social science data services at UCLA from the 1970s. The chapter examines how integrating the SSDA into the Library in 2014 led to a shift of focus toward a service that supports data creation, interpretation and publication regardless of discipline or methodology. It articulates the drivers for change on the UCLA campus that led to the redesign of service offerings and describes how the DSC's involvement with the Carpentries movement expanded its ability to teach data and coding skills. The chapter also reflects on the challenges faced in establishing a service profile that is non-traditional for a library while focusing on building an inclusive community that democratizes data science tools and their research applications.

UCLA: context

UCLA is a public research institution located in Los Angeles, California. UCLA has a diverse community of scholars that encompasses nearly 30,000 undergraduates pursuing 125 majors, 13,000 graduate students in 59 research programs and over 7,000 faculty members. To support its research activities, the University deployed a department-based research support infrastructure. Research data support has been heavily siloed across campus, depending on when and where departments can access resources to support these endeavors. Several distinct groups have emerged that provide different support layers for other disciplines. For example, researchers in STEM (science, technology, engineering and mathematics) fields have ready access to course-integrated resources in campus units such as the UCLA Collaboratory in the Institute for Quantitative and Computational Biology and the Office of Advanced Research Computing. These institutes have large staffs and support thousands of researchers annually.

In contrast, departments in social sciences, humanities and arts lack access to similar institutes or infrastructure. However, data-intensive research is a part of nearly every discipline's research workflow.