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The Practice of Reproducible Research

Case Studies and Lessons from the Data-Intensive Sciences

Justin Kitzes (Editor), Daniel Turek (Editor), Fatma Deniz (Editor)

Available worldwide

Paperback, 368 pages
ISBN: 9780520294752
October 2017
$29.95, £24.95
Other Formats Available:
The Practice of Reproducible Research presents concrete examples of how researchers in the data-intensive sciences are working to improve the reproducibility of their research projects. In each of the thirty-one case studies in this volume, the author or team describes the workflow that they used to complete a real-world research project. Authors highlight how they utilized particular tools, ideas, and practices to support reproducibility, emphasizing the very practical how, rather than the why or what, of conducting reproducible research.
 
Part 1 provides an accessible introduction to reproducible research, a basic reproducible research project template, and a synthesis of lessons learned from across the thirty-one case studies. Parts 2 and 3 focus on the case studies themselves. The Practice of Reproducible Research is an invaluable resource for students and researchers who wish to better understand the practice of data-intensive sciences and learn how to make their own research more reproducible.
Justin Kitzes is Assistant Professor of Biology at the University of Pittsburgh.
 
Daniel Turek is Assistant Professor of Statistics at Williams College.
 
Fatma Deniz is Postdoctoral Scholar at the Helen Wills Neuroscience Institute and the International Computer Science Institute, and Data Science Fellow at the University of California, Berkeley.
“Understanding why science should be open is only the first step; the second is to actually do it. This wide-ranging new book shows how researchers from a variety of disciplines are translating general principles into specific improvements in their work that others can learn from and imitate. Everyone who is trying to squeeze insight out of data will learn something from it, and those who are trying to train the next generation of scientists will find it a rich source of examples and models for their students to emulate.”—Greg Wilson, Cofounder of Software Carpentry, now Principal Consultant with Rangle.io

“The integrity of scientific knowledge depends crucially on the reliability and reproducibility of our published results. But what happens if we don’t even report enough information to allow our experiments to be repeated? This book offers practical solutions to enhance the reporting and validation of research.”—Randy Schekman, Professor, Department of Molecular and Cell Biology, University of California, Berkeley, and Investigator, Howard Hughes Medical Institute

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