Hi Stephanie, Thanks for your email! As Jonah mentioned to be called a Software or Data Carpentry workshop, you do need to use our approved curriculum. There are some options both within and related to our curriculum that would likely be good for your audience however.
First you mention "…what is really needed is the workflow from data processing to analysis in R. .. Teach them how to write code to clean and process data (merge, reshape, etc.) that clearly documents what was done and meets standards of reproducibility. A component on visualization, perhaps a ggplot2 focus, would also be interesting.” and "From my discussions with faculty, they don’t want or need to spend time going over Excel or SQL (Data Carpentry)" Data Carpentry is exactly structured to follow a standard data workflow for a researcher. Workshops use one data set from start to finish and follow a workflow and narrative structure that starts with "so you just got your data" and goes through data organization, data management, data analysis and visualization. We start with Excel not to teach Excel, but to teach researchers how to structure their data so that they can get out of Excel and into tools like R. http://www.datacarpentry.org/spreadsheet-ecology-lesson/00-intro.html We find that as excited as researchers are about many of the tools we teach in Data and Software Carpentry, most don't have their data structured in such a way that they can easily start working with their own data. This lesson, while short, teaches the fundamentals of data organization to enable all the rest of the analyses that we teach. We also teach OpenRefine for data cleaning (a very popular module, and a tool that most researchers haven't been exposed to). Then one full day is on an introduction to R and RStudio and data analysis (with dplyr) and visualization (with ggplot). There's also a Python lesson on the same topics. The SQL lesson does teach the SQL query language, but even more importantly teaches people how to think about databases and the power of managing and querying data. So, I do actually think a standard Data Carpentry would be well-suited to your audience. If this doesn't seem like the right match though, there is also a course on Reproducible Research focused on R. It covers an Introduction to Reproducible Research, Project Organization, Literate programming in R, Version control, automating workflows and sharing and publishing the research workflow. This is a sample workshop and some more information on the materials http://reproducible-science-curriculum.github.io/2015-09-24-reproducible-science-duml/ https://github.com/Reproducible-Science-Curriculum/workshop-planning/blob/master/workshopOverview.md This curriculum was originally developed with NESCent and is in the process of being adopted by Data Carpentry to be one of our standard offerings. http://www.datacarpentry.org/blog/reproducible-research-curriculum/ It hasn't been migrated over yet, so wouldn't be an official workshop, but if you are interested in teaching components of this, folks from #rrhack that were involved in the development of the materials could help. There are also good materials on Reproducible Research from Karl Broman's Tools for Reproducible Research course: http://kbroman.org/Tools4RR/ Thanks so much for your interest in this topic! Best, -Tracy On Tue, May 24, 2016 at 11:36 AM, Stephanie Labou <[email protected]> wrote: > Hi all, > > Thanks for the feedback so far! I have thought about remixing what I need > from SWC/DC/other available sources to put together my own "data bootcamp" > specific to this situation - more time-consuming than I would like, but > certainly doable. If anyone else has suggestions for freely reusable course > materials re: reproducible research focused on R (or if you've done > something like this before), please let me know! > > -Steph > > On Tue, May 24, 2016 at 11:21 AM, W. Trevor King <[email protected]> wrote: > >> On Tue, May 24, 2016 at 05:56:36PM +0000, Jonah Duckles wrote: >> > It must have modules on the Shell, Git and either of Python, R or >> Matlab. >> >> The current website is a bit broader, and allows “Git or Mercurial” >> [1,2], both of which have core SWC lessons [3,4,5]. >> >> And of course, you're free to use any lessons you like in your own >> workshop (they're all CC BY 4.0 / MIT), you just can't brand your >> workshop as SWC without those components [6]. >> >> Cheers, >> Trevor >> >> [1]: http://software-carpentry.org/faq/#core-topics >> [2]: >> https://github.com/swcarpentry/website/blob/727535ec8f98a593d8d9ca7d9b3fe7796796e800/pages/faq.html#L167 >> [3]: http://software-carpentry.org/lessons/ >> [4]: https://github.com/swcarpentry/git-novice >> [5]: https://github.com/swcarpentry/hg-novice >> [6]: http://software-carpentry.org/faq/#trademark >> >> -- >> This email may be signed or encrypted with GnuPG (http://www.gnupg.org). >> For more information, see >> http://en.wikipedia.org/wiki/Pretty_Good_Privacy >> > > > _______________________________________________ > Discuss mailing list > [email protected] > http://lists.software-carpentry.org/listinfo/discuss >
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