Best Practices for Computational Science: Software Infrastructure and Environments for Reproducible and Extensible Research

Authors

  • Victoria Stodden Columbia University
  • Sheila Miguez Columbia University

DOI:

https://doi.org/10.5334/jors.ay

Keywords:

best practices, reproducible research, archiving, data sharing, code sharing, wiki, open science, computational science, scientific method

Abstract

The goal of this article is to coalesce a discussion around best practices for scholarly research that utilizes computational methods, by providing a formalized set of best practice recommendations to guide computational scientists and other stakeholders wishing to disseminate reproducible research, facilitate innovation by enabling data and code re-use, and enable broader communication of the output of computational scientific research. Scholarly dissemination and communication standards are changing to reflect the increasingly computational nature of scholarly research, primarily to include the sharing of the data and code associated with published results. We also present these Best Practices as a living, evolving, and changing document at http://wiki.stodden.net/Best_Practices.

Author Biographies

Victoria Stodden, Columbia University

Assistant Professor, Department of Statistics

Sheila Miguez, Columbia University

Staff Scientist, Department of Statistics

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Published

2014-07-09