Tools: knitr: A Comprehensive Tool for Reproducible Research in R. Reproducibility Using VisTrails. Sumatra: A Toolkit for Reproducible Research. CDE: Automatically Package and Reproduce Computational Experiments. Reproducible Physical Science and the Declaratron. Practices and Guidelines: Developing Open-Source Scientific Practice. Reproducible Bioinformatics Research for Biologists. Reproducible Research for Large-Scale Data Analysis. Practicing Open Science. Reproducibility, Virtual Appliances, and Cloud Computing. The Reproducibility Project: A Model of Large-Scale Collaboration for Empirical Research on Reproducibility—Open Science Collaboration. What Computational Scientists Need to Know about Intellectual Property Law: A Primer. Platforms: Open Science in Machine Learning. RunMyCode.org: A Research-Reproducibility Tool for Computational Sciences. Open Science and the Role of Publishers in Reproducible Research. Index.
Victoria Stodden
"This collection brings together the expertise and experience of
numerous authors and is likely to be valuable to scientists and
statisticians alike. … This book should have broad appeal …
introduces some extremely useful tools and practices from leaders
in the field. On top of that, it also contains an exciting vision
for the future of scientific research. … The challenge of
reproducibility in the computational era is being confronted across
the sciences, with each field developing its own tools and best
practices. This book is an important step in bringing together a
broad group of scientists to share what has been learned."
—Journal of the American Statistical Association, June 2015"The
book as a whole has something for everybody and provides an
interesting snapshot of the available tools, platforms, and good
practices for researchers as the scientific community aims to be
more self-correcting."
—Journal of Statistical Software, October 2014"Three recent books
have significantly influenced how I use R in reproducible work:
Dynamic Documents with R and knitr by Yihui Xie, Reproducible
Research with R and RStudio by Christopher Gandrud, and
Implementing Reproducible Research edited by Victoria Stodden,
Friedrich Leisch, and Roger D. Peng … I recommend all three books
to R users at any level. There really is something here for
everyone."
—Richard Layton, PhD, PE, Rose-Hulman Institute of Technology,
Terre Haute, Indiana, USA"In total, this book provides information
on almost all aspects of reproducible research in the open science
environment … I would recommend this book to anybody who wants to
learn more about reproducible research in the context of open
science."
—Biometrical Journal
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