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Expanding lesson to show how to use JSON script on datasets to enhance understanding of scripts #183
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We would welcome a pull request that addresses the wishes to elaborate on explanation of JSON and opening .zip files, as well as how to incorporate JSON script use into the lesson. |
Debbie
I am new to this process and this suggestion was part of my trainer requirements.
What exactly is a pull request?
How do we move forward?
Thanks
Sara
From: Debbie Paul [mailto:notifications@github.com]
Sent: Monday, August 20, 2018 2:18 PM
To: datacarpentry/OpenRefine-ecology-lesson
Cc: Duke, Sara - ARS; Author
Subject: Re: [datacarpentry/OpenRefine-ecology-lesson] Expanding lesson to show how to use JSON script on datasets to enhance understanding of scripts (#183)
We would welcome a pull request that addresses the wishes to elaborate on explanation of JSON and opening .zip files, as well as how to incorporate JSON script use into the lesson.
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For Sara: i have not worked on zip files in OpenRefine, however i think its possible. But try on one file ata a time then you merge the files, OpenRefine "cleans up"data, filter and sorting- then you can cluster it-The way to contribute to the lessons is to fork the repository update the lesson and make a pull request. You can read more on the process here: |
Closing as idea is implemented by explaining how to apply. Further details about JSON and tar.gz files may be outside the scope. |
There is some technical jargon that is used which is not clearly explained for the novice user. The concept of a script (JSON) and compressed files (tar.gz) are not assumed to be known by students in these workshops. For instance, some of the problems students may have is unzipping a .zip file; which is a fairly common form of compressed file. So while it is said that the scripts can be applied to other datasets-- this would be something that would be useful to show how to apply the script to other datasets.
Would it be possible to divide the data set used for this lesson and apply the script to a second dataset and then merge the two datasets into the one original.
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Please keep in mind that lesson maintainers are volunteers and it may be some time before they can respond to your contribution. Although not all contributions can be incorporated into the lesson materials, we appreciate your time and effort to improve the curriculum. If you have any questions about the lesson maintenance process or would like to volunteer your time as a contribution reviewer, please contact Kate Hertweck (k8hertweck@gmail.com).
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