washr turns a cleaned dataset into a documented R data package that follows the FAIR principles, with a website, a citation file and machine readable metadata. It is the toolkit behind the openwashdata data packages, and it works for any group that publishes open data as an R package.
From CRAN:
install.packages("washr")Or the development version from GitHub:
# install.packages("remotes")
remotes::install_github("openwashdata/washr")The stable core scaffolds and documents the package, one function per step, in the order you run them:
setup_ci() adds the R CMD check workflow the review
standard requires.setup_rawdata() creates data-raw/ and the
processing script.setup_dictionary() writes the variable dictionary from
the data objects.setup_roxygen() writes the roxygen documentation from
the dictionary.update_description() completes DESCRIPTION
to the openwashdata standard.setup_readme() writes the README from the
template.setup_website() writes the pkgdown configuration and
builds the site.use_brand() installs the openwashdata brand for the
site.update_citation() writes the citation files, with the
DOI once there is one.The FAIR layer is one experimental function.
update_metadata() derives a schema.org description of the
dataset from the files above and embeds it in the site, where dataset
search engines read it.
Every function reads what is there, merges its changes, and is safe to run again.
The Get started page walks through the workflow in order, and the Reference page documents each function. The publishing guide covers the same steps with more explanation and the parts outside R, such as the GitHub repository and the Zenodo release.