Building Reproducible Data Packages with DataPackageR

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Author: Greg Finak

“Sharing data sets for collaboration or publication has always been challenging, but it’s become increasingly problematic as complex and high dimensional data sets have become ubiquitous in the life sciences. Studies are large and time consuming; data collection takes time, data analysis is a moving target, as is the software used to carry it out.”
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Read the full post to learn how DataPackageR helps with building R data packages to reproducibly process raw data into packaged, analysis-ready data sets: https://ropensci.org/blog/2018/09/18/datapackager/

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This is really cool!

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Thanks for posting this example. Because DataPackageR has been pulled from CRAN I have forked at copy and am working through it.

Question: Is there a particular reason for using tempdir()? Will a more permanent path work?

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tempdir() was used in the post as an example, to not leave data behind, but in your real work you indeed need to use a more permanent path.

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