#3 Reproducing statistical results · injunctive
“Curation: Where are code and data available? With what expected persistence and longevity? Is there a way to access future updates, for example, a version-control repository of the code base?” (p. 11)
#4 Storing reproducible results from computational experiments using scientific python packages · tacit
“get_git_revision()” listed as a captured metadata field (Fig.3, p.48); separately, of their own package: “The source code is under version control using Git” (p.49)
#26 Facilitating reproducible project management and manuscript development in team science: the projects R package · tacit
“users interested in version control can utilize version control capabilities integrated with RStudio (e.g., Git, Subversion) as they would with any other RStudio-housed project” (p.7)
#38 Ten simple rules for writing dockerfiles for reproducible data science · injunctive
“As plain text files, Dockerfiles are well suited for use with version control systems. Including a Dockerfile alongside your code and data is an effective way to consistently build your software” (p. 15-16)
#51 A reproducible data analysis workflow with R Markdown, Git, Make, and Docker · injunctive
Same goal-3 quote as Data/Code deposit above (p.1); mechanism described p.6: “Version control manages changes to files… over time so that you can recall specific versions of files later”
#54 WORCS: a workflow for open reproducible code in science · injunctive
“An integral part of WORCS is the explicit version control software Git” (p. 32)
#63 Toward practical transparent verifiable and long-term reproducible research using guix · injunctive
“these channels are imperatively versioned and their history is tracked by the Git version control system” (p.4)
#69 The interdependence of data producers and data users: how researchers’ behaviors can support or hinder each other · injunctive
“Use software systems that enable versioning and tracking of data and code” (Table 3, p.24)
#108 Checklists for computational reproducibility in social sciences: insights from literature and survey evaluation · injunctive
“Using version control tool e.g., Git.” (Checklist 2)
#117 Computational reproducibility of R code supplements on OSF · injunctive
“the absence of robust version control systems… make it challenging to replicate the computational environment used in these studies” (p. 2)
#120 Reproducibility spectrum for applied social sciences: conceptual taxonomy and recommended tools · tacit
“Version control and sharing of analysis scripts”; “share on GitHub” listed as step 2
#131 Guide for Accelerating Computational Reproducibility in the Social Sciences · tacit
“Set up the reproduction package using version control software, such as Git.” and “When reporting your improvements in the SSRP, we suggest using version control software (git) to track the differences between the original reproduction package and your proposed improvements”