[data-carpentry-discuss] Organizing Data Carpentry workshop - advice

Wed Jan 28 19:40:11 PST 2015

Hi Leah,

That's great there's good interest! I agree with Ethan both that the 
lessons for Python and R are redundant and that it would be tough to 
teach both languages in two days. Maybe the question is more, what are 
people looking to do? Are they doing statistical analysis and data 
visualization with ecological data? If so, then R might be better. If 
they want to write scripts for data parsing or work with a lot of 
colleagues who are working in Python, that might be better.

As Kai says, the current Data Carpentry workshop components are focused 
on data organization/management and the data 
analysis/presentation/visualization.

The current modules are:

- spreadsheets for data organization
- OpenRefine for data cleaning (30 minute demo)
- SQL for managing and querying data
- introduction to R or Python for data analysis and visualization
- the shell for automation

If you wanted to be able to spend more time on R or Python, which we're 
finding people are interested in, especially being able to get through 
more of the data visualization, you could leave out the shell or SQL and 
use that extra time for R or Python.

The mix of experience is always a challenge. Data Carpentry lessons 
right now have been developed for people with little to no prior 
computational experience, so no prior experience is expected or 
required. This means things can be a little slower for people who do 
have some experience, but has the advantage that we're clear about the 
level up front and it doesn't leave as many people behind. People with 
more experience still learn new tips and tricks for the things they've 
seen already and can help their neighbors, and often even if someone is 
experience with one tool, they might be new to another - so maybe they 
know SQL well, but haven't worked in R before.

This focus on learners newer to computation, does mean, as Ethan 
mentioned that we're also not currently teaching git. As a concept, it's 
more advanced than what most people new to programming are ready for.  
We have talked about adding to the R lesson a component about working 
with github from within RStudio, as that takes away some of the 
complexity, but haven't had a chance to develop that or try it out yet.

Does this approach and modules seem like it matches with what the people 
there need?

Best,
-Tracy
> Hsi-Kai (Kai) Yang <mailto:hky2 at uw.edu>
> January 28, 2015 at 5:25 PM
> Leah:
> You might want to focus on either (1) data 
> preparation/munging/management, or (2) data analysis/presentation. 
> Data exploration probably is in between the two areas.
> It could be too aggressive trying to cover all aspects of data science 
> in two days.
> Also you might want to assume the attendees can master at least one 
> programming language. I believe learning how to program belongs to 
> software carpentry. Data carpentry is all about data science.
> My 2 cent.
> Thanks.
> -kai
>
>
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> Leah Wasser <mailto:lwasser at neoninc.org>
> January 28, 2015 at 12:09 AM
> HI Tracey, and fellow DC participants.
> I am looking for some advice. There has been ongoing interest in a 
> Data Carpentry workshop at NEON (where i work for those of you who 
> don't know me). :)
>
> The challenge that I see at this point, is figuring out what content 
> would be most relevant. I posted a survey today and already have a 
> handful of responses - all interested in a 2 day workshop.
>
> However there is a mix of interest in Python vs R. And some mix of 
> background (mostly intermediate focused however).
>
> I am giving everyone a week to respond to the survey. Then I need to 
> figure out an approach. Depending upon the volume of responses, i am 
> even thinking about something that is split across days (R one day, 
> python another). Git and shell combined? OR SQL ? Can anyone help 
> guide me through the logistics of deciding the best approach for this 
> workshop once the survey results are in?
>
> Thank you in advance!!
> leah
>
> Leah A. Wasser, Ph.D.
> Remote Sensing Ecologist
> Senior Science Educator - Universities
> National Ecological Observatory Network (NEON)
> Boulder, Colorado
>
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> Today's Topics:
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> 1. Data Carpentry Genomics and Assessment hackathon (Tracy Teal)
>
>
> ----------------------------------------------------------------------
>
> Message: 1
> Date: Tue, 27 Jan 2015 10:34:30 -0500
> From: Tracy Teal <tkteal at datacarpentry.org>
> Subject: [data-carpentry-discuss] Data Carpentry Genomics and
> Assessment hackathon
> To: discuss at datacarpentry.org
> Message-ID: <54C7B006.4060605 at datacarpentry.org>
> Content-Type: text/plain; charset=windows-1252; format=flowed
>
> If you're working or interested in genomics or assessment, we hope
> you'll consider applying for our upcoming Data Carpentry Genomics and
> Assessment hackathon. We?re very excited about this event and the
> opportunity to develop lessons targeting genomics researchers and build
> assessment in to the curriculum. Travel support is available. Please
> apply to participate!
>
> Dates: March 23-25, 2015
> Location: Cold Spring Harbor Labs, NY
>
> It's a short application and the deadline is this Friday, January 30th.
>
> Call for Participation:
> https://docs.google.com/document/d/1r5Bfc-Igt7Hd8kjXsuPw7SenOHkxIQbEDbtnZfAxXbA/pub
>
> Application:
> https://docs.google.com/forms/d/17cSQyPIvTIhCQGrFLRoQ0kSway1ZyxgRm9QL85BW8v8/viewform
>
> If you have any questions about the event, please let me know!
>
> Best,
> -Tracy
>
>
>
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