Carob

Create reproducible workflows that reshape primary agricultural research data from experiments and surveys into a standard format, and to aggregate individual data sets into larger collections that can be used in further research.
https://github.com/carob-data/carob

Category: Consumption
Sub Category: Agriculture and Nutrition

Last synced: about 10 hours ago
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Carob: standardizing agricultural research data

README.md

Carob

Carob creates reproducible workflows that standardize primary agricultural research data from experiments and surveys. Standardization includes the use of a common file format, variable names, units and accepted values according to the terminag standard. Standardized data sets are aggregated into larger collections that can be used in further research. We do this by writing an R script for each individual dataset. See the website for more information.

Carob is an open access Extract, Transform, and Load (ETL) framework supported by CGIAR to support predictive analytics (machine learning, artifical intelligence) and other types of data analysis.

Contributions are welcome from anyone, and they can be made via pull-requests. Feel free to improve these scripts, or provide new ones. See the instructions on how to write a Carob script described here. You can also raise an issues. A good place to discover new data sets is the Gardian website or our to-do list.

Get the data

Compiled versions of the dataset can be downloaded from carob-data.org (data with a CC license only) and some will eventually be made available on the carob dataverse.

You can also compile your own version by cloning this repo and running

remotes::install_github("carob-data/carobiner")
ff <- carobiner::make_carob(path)

where path is the folder of the cloned repo (e.g. "d:/github/carob")


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Past year average time to close issues: 1 day
Past year average time to close pull requests: about 15 hours
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Past year average comments per issue: 1.5
Past year average comments per pull request: 0.8
Past year merged pull request: 187
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