Description

Book Synopsis

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.



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

Data Science in the Library: Tools and Strategies

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    Order before 4pm today for delivery by Wed 12 Aug 2026.

    A Paperback / softback by Joel Herndon

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      Publisher: Facet Publishing
      Publication Date: Publication Date: 20/12/2021
      ISBN13: 9781783304592, 978-1783304592
      ISBN10: 1783304596

      Description

      Book Synopsis

      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.



      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

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