GESIS Leibniz-Institut für Sozialwissenschaften, Mannheim, Germany.
PLoS One. 2023 Jun 8;18(6):e0286761. doi: 10.1371/journal.pone.0286761. eCollection 2023.
A complete declarative description of the computational environment is usually 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 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).
当研究人员共享他们的材料时，通常会缺少对计算环境的完整说明。如果没有这样的描述，软件过时和缺少系统组件可能会危及未来的计算可重复性，即使有数据和计算机代码可用。R 包 rang 是一个完整的解决方案，可生成说明性描述，以便其他研究人员能够自动在特定时间点重建计算环境。基于 Docker 的重建过程已经针对 2001 年的 R 代码进行了测试。rang 生成的说明性描述满足可重现研究纲要的定义，可以作为研究纲要进行共享。在本文中，我们将展示如何使用 rang 使原本无法执行的代码（涵盖计算社会科学和生物信息学等领域）再次可执行。我们还提供了有关如何使用 rang 构建当前研究的可重现和可共享研究纲要的说明。该软件包目前可从 CRAN（https://cran.r-project.org/web/packages/rang/index.html）和 GitHub（https://github.com/chainsawriot/rang）获得。
