Data Science in the Library
Tools and Strategies for Supporting Data-Driven Research and Instruction
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Product details:
- Edition number 1
- Publisher Facet Publishing
- Date of Publication 20 December 2021
- ISBN 9781783304608
- Binding Hardback
- No. of pages224 pages
- Size 234x156 mm
- Language English 222
Categories
Short description:
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.
MoreLong description:
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.
MoreTable 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
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