Data Science In The Library: Tools and Strategies for Supporting Data-Driven Research and Instruction

by Joel Herndon (Editor)

Overview

While there is a growing literature that explores the technical details of data science and the growing methodological concerns, there have been few works that explore how these changes are influencing the work of library and information specialists and faculty.

This book considers the current environment for data driven research, instruction, and consultation from a variety of faculty and library perspectives and suggests strategies for engaging with the tools and methods of data driven research. By combining case studies on data science instruction/consultation with suggestions for best practices, this book contributes to the larger literature on integrating data science training, consultation, programming, and services into both library and university programs.

Product Details

ISBN-13:	9781783304592
Publisher:	American Library Association
Publication date:	07/18/2022
Pages:	176
Product dimensions:	6.14(w) x 9.21(h) x 0.70(d)

About the Author

Joel Herndon leads Duke Libraries' Data and Visualization Services, a consulting and training service providing support for data science, data management, data visualization, digital mapping, and data analysis. His recent research considers the evolution of data management requirements in social science journals and how research libraries can provide consultation and training to meet those requirements (Herndon and O'Reilly, 2016). He has a strong interest in how libraries engage with their communities in digital research and training. Recent projects include leading the launch of the Edge research space in Duke Libraries, active involvement in Duke's DataFest competitions, and serving as a principal investigator on the Data Curation Network.

Table of Contents

PART 1: DATA SCIENCE AND RESEARCH LIBRARIES – PERSPECTIVES; Sustainability and Success Models for Informal Data Science Training within Libraries; The Fundación Juan March DataLab: A Data Science Unit within a Research Support Library; PART 2: DATA SCIENCE INSTRUCTION; Toward Reproducibility: Academic Libraries and Open Science; Start with Data Science; PART 3: DATA SCIENCE SERVICES; In Support of Data-Intensive Science at the University of Washington; From a Data Archive to Data Science: Supporting Current Research; PART 4: DESIGNING AND STAFFING DATA SCIENCE; In-House Training as the First Step to Becoming a Data Savvy Librarian; Designing for Data Science: Planning for Library Data Services

Editorial Reviews

”These [case studies] offer important insights into how libraries developed staffing and expertise, provisioned infrastructure, provided services and instruction, and—most important—collaborated with other units on campus and with organizations outside their institutions ... In sum, this book will be useful to a wide variety of libraries and librarians, whether or not they have launched their own data science initiatives.”
— Choice

From the Publisher