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.
Highlights
Academia is arguably past the tipping point of a paradigm shift towards open science
Version control is a near-essential tool for scientific reproducibility, as anyone learns who has had the experience of accidentally deleting a crucial file, or of being unable to reproduce analyses because they ran some analyses interactively, instead of documenting the syntax in a script file
This is important because most major preprint servers – including arXiv.org and all preprint services hosted by the Open Science Framework (OSF) – are indexed by Google Scholar
Summary
Academia is arguably past the tipping point of a paradigm shift towards open science Support for this transition was first motivated by several highly publicized cases of scientific fraud (Levelt et al [20]), increasing awareness of questionable research practices (John et al [16]), and the replication crisis (Shrout and Rodgers [36]). This paper is designed to ease that transition by presenting a simple workflow, based on established best practices, that meets most requirements open science: The Workflow for Open Reproducible Code in Science (WORCS). This paper is most relevant for scholars using R to conduct research that involves academic prose, analysis code, and tabular data For other readers, it can serve as a primer on open science workflows, and provide a sensible starting point for a customized solution. It can be used by individual authors to produce work in accordance with best practices in the absence of top-down support or guidelines (i.e., “grass roots” open science)
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