Last updated: 2018-10-17

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  • ✖ R Markdown file: uncommitted changes The R Markdown is untracked by Git. To know which version of the R Markdown file created these results, you’ll want to first commit it to the Git repo. If you’re still working on the analysis, you can ignore this warning. When you’re finished, you can run wflow_publish to commit the R Markdown file and build the HTML.

  • ✔ Repository version: 99529cf

    Great! You are using Git for version control. Tracking code development and connecting the code version to the results is critical for reproducibility. The version displayed above was the version of the Git repository at the time these results were generated.

    Note that you need to be careful to ensure that all relevant files for the analysis have been committed to Git prior to generating the results (you can use wflow_publish or wflow_git_commit). workflowr only checks the R Markdown file, but you know if there are other scripts or data files that it depends on. Below is the status of the Git repository when the results were generated: 
    
Ignored files:
    Ignored:    .Rhistory
    Ignored:    .Rproj.user/
    Ignored:    docs/figure/

Untracked files:
    Untracked:  .DS_Store
    Untracked:  analysis/intro.Rmd
    Untracked:  assets/Packaging-Data-Analytical Work-Reproducibly-Using-R-and-Friends.pdf
    Untracked:  assets/marw_f1.jpeg
    Untracked:  assets/marw_f2.jpeg
    Untracked:  assets/marw_f3.jpeg
    Untracked:  assets/marw_f4.jpeg
    Untracked:  code/dev.R

Staged changes:
    New:        assets/peerj-preprints-3192.pdf
    Note that any generated files, e.g. HTML, png, CSS, etc., are not included in this status report because it is ok for generated content to have uncommitted changes.

Scholarship will be strengthened if we are more open with research materials, yet we lack conventions and technical infrastructure for such openness.

R packages can be used as a research compendium for organising and sharing files. R package structure is uniquely suitable to being easily adapted to solve problems of organising les and sharing them with other researchers. We describe how the conventional structure of R packages can be adapted for use as a research compendium, and illustrate this use with real-world examples.

Research Compendium? Three Generic Principles

  1. organize its les according to the prevailing conventions of the scholarly community: help other people recognize the structure of the project, and also support tool building which takes advantage of the shared structure.
  2. clear separation of data, method, and output, while unambiguously expressing the relationship between those three.
  3. A research compendium should specify the compu- tational environment that was used for the original analysis

History

This reproducible R Markdown analysis was created with workflowr 1.0.1