Medical School Office Building (MSOB)
|DATE:||May 10, 2018|
|TIME:||1:30 - 2:50 pm|
|TITLE:||The workflowr R package: a framework for reproducible and collaborative data science|
Department of Human Genetics, University of Chicago
The workflowr R package helps organize computational research in a way that promotes effective project management, reproducibility, collaboration, and sharing of results. Workflowr combines literate programming (knitr and rmarkdown) and version control (Git, via git2r) to generate a website containing time-stamped, versioned, and documented results. Any R user can quickly and easily adopt workflowr, which includes four key features: (1) workflowr automatically creates a directory structure for organizing data, code, and results; (2) workflowr uses the version control system Git to track different versions of the code and results without the user needing to understand Git syntax; (3) to support reproducibility, workflowr automatically includes code version information in webpages displaying
results and; (4) workflowr facilitates online Web hosting (e.g. GitHub Pages) to share results. Our goal is that workflowr will make it easier for researchers to organize and communicate reproducible results. Documentation and source code are available at https://github.com/jdblischak/workflowr.
Lowndes et al., 2017. Our path to better science in less time using open data science tools. https://www.ncbi.nlm.nih.gov/pubmed/28812630
Donoho, 2010. An invitation to reproducible computational research.