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Implementing Reproducible Research

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accurately reproduce a scientific result
BioMed Central
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Cloud Computing
cloud computing in reproducible research
cloud-based scientific workflows
Code Chunks
computational science methods
conducting and distributing reproducible research
Current Intellectual Property Law
Distributed Version Control Systems
DVCS
empirical research replication
Encode Consortium
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Full Text Open Access
HEC Paris
IPython Notebook
National Library
open data licensing
Open Source
Open Source Model
Open Source Software
PDF Publication
Pull Request
Replication Teams
reproducibility in computational science
reproducible computational experiments guide
Reproducible Research
reproducible research in bioinformatics and large-scale data analyses
Reproducible Research Standard
Research Articles
scientific data sharing
scientific programming practices
STM Publishing
VCS
Version Control
Version Control Systems

Product details

  • ISBN 9780367576172
  • Weight: 453g
  • Dimensions: 156 x 234mm
  • Publication Date: 30 Jun 2020
  • Publisher: Taylor & Francis Ltd
  • Publication City/Country: GB
  • Product Form: Paperback
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Description

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.

About
Victoria Stodden