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Implementing Reproducible Research

Stodden, Victoria , editor.

Implementing Reproducible Research

Stodden, Victoria , editor.

9781315373461

First edition.

1 online resource (448 pages) : 60 illustrations, text file, PDF.

Chapman & Hall/CRC The R Series

Chapman & Hall/CRC The R Series.

Toolsknitr: A Comprehensive Tool for Reproducible Research in R Yihui XieReproducibility Using VisTrails Juliana Freire, David Koop, Fernando Chirigati, and Cludio T. SilvaSumatra: A Toolkit for Reproducible Research Andrew P. Davison, Michele Mattioni, Dmitry Samarkanov, and Bartosz TeleczukCDE: Automatically Package and Reproduce Computational Experiments Philip J. GuoReproducible Physical Science and the Declaratron Peter Murray-Rust and Dave Murray-Rust -- Practices and GuidelinesDeveloping Open-Source Scientific Practice K. Jarrod Millman and Fernando PrezReproducible Bioinformatics Research for Biologists Likit Preeyanon, Alexis Black Pyrkosz, and C. Titus BrownReproducible Research for Large-Scale Data Analysis Holger Hoefling and Anthony RossiniPracticing Open Science Luis Ibanez, William J. Schroeder, and Marcus D. HanwellReproducibility, Virtual Appliances, and Cloud Computing Bill HoweThe 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 Victoria Stodden -- PlatformsOpen Science in Machine Learning Mikio L. Braun and Cheng Soon OngRunMyCode.org: A Research-Reproducibility Tool for Computational Sciences Christophe Hurlin, Christophe Prignon, and Victoria StoddenOpen Science and the Role of Publishers in Reproducible Research Iain Hrynaszkiewicz, Peter Li, and Scott Edmunds -- Index.

In computational science, reproducibility requires that researchers make code and data available to others so that the data can be analyzed in a similar manner as in the original publication. Code must be available to be distributed, data must be accessible in a readable format, and a platform must be available for widely distributing the data and code. In addition, both data and code need to be licensed permissively enough so that others can reproduce the work without a substantial legal burden. Implementing Reproducible Research covers many of the elements necessary for conducting and distributing reproducible research. It explains how to accurately reproduce a scientific result. Divided into three parts, the book discusses the tools, practices, and dissemination platforms for ensuring reproducibility in computational science. It describes: Computational tools, such as Sweave, knitr, VisTrails, Sumatra, CDE, and the Declaratron system open source practices, good programming practices, trends in open science, and the role of cloud computing in reproducible research Software and methodological platforms, including open source software packages, RunMyCode platform, and open access journals Each part presents contributions from leaders who have developed software and other products that have advanced the field. Supplementary material is available at www.ImplementingRR.org.

Reproducible research.

Research -- Statistical methods.

accurately reproduce a scientific result.

cloud computing in reproducible research.

conducting and distributing reproducible research.

Reproducible Research Standard.

reproducibility in computational science.

reproducible research in bioinformatics and large-scale data analyses.

Electronic books.

Stodden, Victoria ,

Leisch, Friedrich,

Peng, Roger D.,

Taylor and Francis.

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