Reproducible computing with rctrack: Software package addresses fundamental scientific challenges of Big Data era.

Published descriptions of data sets and analysis procedures are helpful ways to ensure scientific results are reproducible. Unfortunately the collection and provision of this information is often provided by researchers in retrospect and can be fraught with uncertainty. The only solution to this problem is to computationally collect and archive data files, code files, result files, and other details while the data analysis is being performed. Stan Pounds highlights the release of rctrack, a software package that automatically enables this file collection for analyses performed with the open-source R programming language, thereby minimizing the burden of collecting and archiving details.