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



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.

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.

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