20 Reproducibility and Provenance

20.1 Learning Objectives

In this lesson, you will learn:

• About the importance of computational reproducibility
• The role of provenance metadata
• Tools and techniques for reproducibility supportred by the Arctic Data Center
• How to build a reproducible paper in RMarkdown

A great overview of this approach to reproducible papers comes from:

• Ben Marwick, Carl Boettiger & Lincoln Mullen (2018) Packaging Data Analytical Work Reproducibly Using R (and Friends), The American Statistician, 72:1, 80-88, doi:10.1080/00031305.2017.1375986

This lesson will draw from existing materials:

• Accelerating synthesis science through reproducible science practices
• rrtools
• Reproducible papers with RMarkdown

To start a reproducible paper with rrtools, run:

devtools::install_github("benmarwick/rrtools")
setwd("..")
rrtools::use_compendium("arcticpaper")

Then, add some more structure to the package:

usethis::use_apl2_license(name="Matthew B. Jones")
rrtools::use_readme_rmd()
rrtools::use_analysis()

Now write a reproducible paper!