Packaging Data Analytical Work Reproducibly Using R (and Friends)

ABSTRACT

Computers are a central tool in the research process, enabling complex and large-scale data analysis. As computer-based research has increased in complexity, so have the challenges of ensuring that this research is reproducible. To address this challenge, we review the concept of the research compendium as a solution for providing a standard and easily recognizable way for organizing the digital materials of a research project to enable other researchers to inspect, reproduce, and extend the research. We investigate how the structure and tooling of software packages of the R programming language are being used to produce research compendia in a variety of disciplines. We also describe how software engineering tools and services are being used by researchers to streamline working with research compendia. Using real-world examples, we show how researchers can improve the reproducibility of their work using research compendia based on R packages and related tools.

KEYWORDS:

• Computational science
• Data science
• Open source software
• Reproducible research

Acknowledgments

This essay originated in discussions at the 2015 rOpenSci unconference (https://github.com/ropensci/unconf/issues/11 and https://github.com/ropensci/unconf/issues/31). Thanks to those who were part of these discussions and helped to broaden our understanding of compendia and R packages. BM was also supported by an Australian Research Council Future Fellowship (FT140100101).