The FAIRification of research in real-world evidence: A practical
introduction to reproducible analytic workflows using Git and R
Abstract
Transparency and reproducibility are major prerequisites for conducting
meaningful real-world evidence (RWE) studies that are fit for
decision-making. Many advances have been made in the documentation and
reporting of study protocols and results, but the principles for version
control and sharing of analytic code in RWE are not yet as established
as in other quantitative disciplines like computational biology and
health informatics. In this practical tutorial, we aim to give an
introduction to distributed version control systems (VCS) tailored
towards the FAIR ( Findable, Accessible,
Interoperable and Reproducible) implementation of RWE
studies. To ease adoption, we provide detailed step-by-step instructions
with practical examples on how the Git VCS and R programming language
can be implemented into RWE study workflows to facilitate reproducible
analyses. We further discuss and showcase how these tools can be used to
track changes, collaborate, disseminate and archive RWE studies through
dedicated project repositories that maintain a complete audit trail of
all relevant study documents.