Data Science in the Library: Tools and Strategies for Supporting Data-Driven Research and Instruction

Author:   Joel Herndon
Publisher:   Facet Publishing
ISBN:  

9781783304592


Pages:   176
Publication Date:   20 December 2021
Format:   Paperback
Availability:   In Print   Availability explained
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Data Science in the Library: Tools and Strategies for Supporting Data-Driven Research and Instruction


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Overview

In the last decade, data science has generated new fields of study and transformed existing disciplines. As data science reshapes academia, how can libraries and librarians engage with this rapidly evolving, dynamic form of research? Can libraries leverage their existing strengths in information management, instruction, and research support to advance data science? Data Science in the Library: Tools and Strategies for Supporting Data-Driven Research and Instruction brings together an international group of librarians and faculty to consider the opportunities afforded by data science for research libraries. Using practical examples, each chapter focuses on data science instruction, reproducible research, establishing data science services and key data science partnerships. This book will be invaluable to library and information professionals interested in building or expanding data science services. It is a practical, useful tool for researchers, students, and instructors interested in implementing models for data science service that build community and advance the discipline.

Full Product Details

Author:   Joel Herndon
Publisher:   Facet Publishing
Imprint:   Facet Publishing
ISBN:  

9781783304592


ISBN 10:   1783304596
Pages:   176
Publication Date:   20 December 2021
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   In Print   Availability explained
This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us.

Table of Contents

PART 1: DATA SCIENCE AND RESEARCH LIBRARIES – PERSPECTIVES Sustainability and Success Models for Informal Data Science Training within Libraries Elizabeth Wickes The Fundación Juan March DataLab: A Data Science Unit within a Research Support Library Luis Martínez-Uribe, Paz Fernández and Fernando Martínez PART 2: DATA SCIENCE INSTRUCTION Toward Reproducibility: Academic Libraries and Open Science Joshua Quan Start with Data Science Mine Çetinkaya-Rundel PART 3: DATA SCIENCE SERVICES In Support of Data-Intensive Science at the University of Washington Jenny Muilenburg From a Data Archive to Data Science: Supporting Current Research Tim Dennis, Zhiyuan Yao, Leigh Phan, Kristian Allen, Jamie Jamison, Doug Daniels and Ibraheem Ali PART 4: DESIGNING AND STAFFING DATA SCIENCE In-House Training as the First Step to Becoming a Data Savvy Librarian Jeannette Ekstrøm Designing for Data Science: Planning for Library Data Services Joel Herndon

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"


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


Author Information

Joel Herndon is the Director of the Center for Data and Visualization Sciences (CDVS) at Duke University Libraries where he leads a library data science program providing support for data visualization, data management, digital mapping, and computational research support. Joel's research focuses on how universities can improve data sharing and data science initiatives through partnerships, training, infrastructure, and project support.

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