Thanks Hao!

-Robert

On Sat, Jan 26, 2019, 12:09 AM Hao Ye <[email protected] wrote:

> Hi,
>
> The requirements for a Data Carpentry workshop are listed at
> https://datacarpentry.org/workshops/
>
> Data Carpentry workshops must include:
>>
>>    - A Data Carpentry lesson on data organization
>>    - Three other modules in the same domain from the Data Carpentry
>>    curriculum
>>    - Be taught by at least one certified Carpentries instructor
>>
>> and for Software Carpentry at https://software-carpentry.org/lessons/
>
> A Software Carpentry workshop is taught by two trained and badged
>> instructors. Over two days, they teach our three core topics: the Unix
>> shell, version control with Git, and a programming language (Python or R).
>
>
> The "R for Reproducible Scientific Analysis" lesson in Software Carpentry
> is pretty flexible, and you can arrange the modules to cover much the same
> content as an R-focused Data Carpentry workshop (though it will use the
> gapminder dataset instead of one with an ecology-, genomics-, social
> science- , etc. focus. That is one option.
>
> I think another option would be to run a normal 2-day Data Carpentry
> workshop, and have an optional supplemental half-day on using Git and
> GitHub.
>
> Best,
> --
> Hao Ye
> [email protected]
>
>
> On Fri, Jan 25, 2019 at 10:05 PM Robert M. Flight <[email protected]>
> wrote:
>
>> Hi Everyone,
>>
>> I couldn't find this specific answer searching my email, and it looks to
>> have moved on the website as well.
>>
>> What topics are required to keep the branding of Software / Data
>> Carpentry??
>>
>> I am part of a self organized Data Carpentry R ecology workshop, and we
>> are debating what topics to teach. The curriculum is data organization,
>> openrefine, R, and SQL.
>>
>> I haven't taught one before, and I haven't dug into the lessons yet, and
>> how they are integrated one with another, but we were thinking it would be
>> good to introduce Git version control, especially in the context of R
>> scripts for data analysis.
>>
>> So how much can we deviate from the curriculum and still be a Data
>> Carpentry workshop, and has anyone else attempted this before??
>>
>> If I was going to do it, my preference would be to remove the OpenRefine
>> lesson and insert a lesson on Git integrated into the R lessons.
>>
>> Thoughts??
>>
>> Thanks in advance,
>>
>> - Robert
>>
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