RANG: Reconstructing reproducible R computational environments

TL;DR

RANG is an R package that creates complete, declarative descriptions of computational environments, enabling researchers to easily reconstruct and share reproducible research setups using Docker, even for very old code.

Contribution

The paper introduces RANG, a novel R package that automates the creation of reproducible environment descriptions, facilitating long-term reproducibility of R code and research compendia.

Findings

Successfully reconstructed R environments dating back to 2001.

Enabled execution of previously unexecutable code across diverse fields.

Provided practical instructions for creating shareable research compendia.

Abstract

A complete declarative description of the computational environment is often missing when researchers share their materials. Without such description, software obsolescence and missing system components can jeopardize computational reproducibility in the future, even when data and computer code are available. The R package rang is a complete solution for generating the declarative description for other researchers to automatically reconstruct the computational environment at a specific time point. The reconstruction process, based on Docker, has been tested for R code as old as 2001. The declarative description generated by rang satisfies the definition of a reproducible research compendium and can be shared as such. In this contribution, we show how rang can be used to make otherwise unexecutable code, spanning from fields such as computational social science and bioinformatics, executable again. We also provide instructions on how to use rang to construct reproducible and shareable research compendia of current research. The package is currently available from CRAN (https://cran.r-project.org/web/packages/rang/index.html) and GitHub (https://github.com/chainsawriot/rang).