Construct Reproducible Analytic Data Sets as R Packages

A framework to help construct R data packages in a reproducible manner. Potentially time consuming processing of raw data sets into analysis ready data sets is done in a reproducible manner and decoupled from the usual 'R CMD build' process so that data sets can be processed into R objects in the data package and the data package can then be shared, built, and installed by others without the need to repeat computationally costly data processing. The package maintains data provenance by turning the data processing scripts into package vignettes, as well as enforcing documentation and version checking of included data objects. Data packages can be version controlled on 'GitHub', and used to share data for manuscripts, collaboration and reproducible research.


Reference manual

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install.packages("DataPackageR")

0.16.2 by Dave Slager, 10 months ago


https://github.com/ropensci/DataPackageR, https://docs.ropensci.org/DataPackageR/


Report a bug at https://github.com/ropensci/DataPackageR/issues


Browse source code at https://github.com/cran/DataPackageR


Authors: Greg Finak [aut, cph] (Original author and creator of DataPackageR) , Paul Obrecht [ctb] , Ellis Hughes [ctb] , Jimmy Fulp [ctb] , Marie Vendettuoli [ctb] (ORCID: , Dave Slager [ctb, cre] , Jason Taylor [ctb] , Kara Woo [rev] (Kara reviewed the package for rOpenSci , see <https://github.com/ropensci/onboarding/issues/230>) , William Landau [rev] (William reviewed the package for rOpenSci , see <https://github.com/ropensci/onboarding/issues/230>)


Documentation:   PDF Manual  


MIT + file LICENSE license


Imports cli, desc, digest, knitr, pkgbuild, pkgload, rmarkdown, roxygen2, rprojroot, usethis, utils, yaml

Suggests covr, data.tree, spelling, testthat, withr

System requirements: pandoc - https://pandoc.org


See at CRAN