WORCS: A workflow for open reproducible code in science

Abstract

Adopting open science principles can be challenging, requiring conceptual education and training in the use of new tools. This paper introduces the Workflow for Open Reproducible Code in Science (WORCS): A step-by-step procedure that researchers can follow to make a research project open and reproducible. This workflow intends to lower the threshold for adoption of open science principles. It is based on established best practices, and can be used either in parallel to, or in absence of, top-down requirements by journals, institutions, and funding bodies. To facilitate widespread adoption, the WORCS principles have been implemented in the R package worcs, which offers an RStudio project template and utility functions for specific workflow steps. This paper introduces the conceptual workflow, discusses how it meets different standards for open science, and addresses the functionality provided by the R implementation, worcs. This paper is primarily targeted towards scholars conducting research projects in R, conducting research that involves academic prose, analysis code, and tabular data. However, the workflow is flexible enough to accommodate other scenarios, and offers a starting point for customized solutions. The source code for the R package and manuscript, and a list of examplesof WORCS projects, are available at https://github.com/cjvanlissa/worcs.

Reproducible Research in R: A Tutorial on how to Do the Same Thing More Than Once

“…One would hope that sharing a dynamic document would allow individuals (including one's future self) to simply download and reproduce a given analysis. While version control and dynamic document generation are becoming more common, we have argued that two more components are required and that each component alone is unlikely to guarantee reproducibility [1,17]. In practice, dependencies between project files (for example, the information what script uses which data file and what script needs to be run first) or on external software (such as system libraries or components of the programming language, such as other R packages) are frequently unmentioned or not exhaustively and unambiguously documented.…”

“…Make therefore offers a standardized process to reproduce projects, regardless of the complexity or configuration of the project. Note that the Workflow for Open Reproducible Code in Science (WORCS) we presented elsewhere [17] does not contain this element of dependency tracking explicitly but its strict structure of only containing one definite R Markdown still makes dependencies between files unambiguous.…”

“…A more comprehensive overview of the use of containarization in research projects is given by Wiebels and Moreau [21]. Note that the Workflow for Open Reproducible Code in Science (WORCS) we presented elsewhere [17] relies for software management on the R package renv [22] which is more lightweight and easier to use on the one hand, but not as comprehensive on the other hand because it only snapshots the R packages instead of all software used.…”

WORCS: A Workflow for Open Reproducible Code in Science

“…WORCS is, first and foremost, a conceptual workflow that could be implemented in any software environment. As of this writing, the workflow has been implemented for R users in the package worcs (Van Lissa et al [41]). Several arguments support our choice to implement this workflow first in R and RStudio, although we encourage developers to port the software to other languages.…”

“…The principles underlying this workflow are universal and largely platform independent. We also present a software implementation of WORCS for R users (R Core Team [31]): The R package worcs (referred to in monospace font, Van Lissa et al [41]). This package offers a project template for RStudio (RStudio Team [35]), and several convenience functions to automate specific workflow steps.…”