Author: Michael Sumner
“In May 2019 version 0.2.0 of tidync was approved by rOpenSci and accepted to CRAN. Here we provide a quick overview of the typical workflow with some pseudo-code for the main functions in tidync. This overview is enough to read if you just want to try out the package on your own data. The tidync package is focussed on efficient data extraction for developing your own software, and this somewhat long post takes the time to explain the concepts in detail.
There is a section about the NetCDF data model itself. Then there is a detailed illustration of a raster data set in R including some of the challenges faced by R users. This is followed by sections on how tidync sees metadata and coordinates in NetCDF, how we can slice a dataset and control the format of the output. We then discuss some limitations and future work, and then (most importantly) reflect on the rOpenSci process of package review.
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Read the full post: https://ropensci.org/blog/2019/11/05/tidync/