Name: Reproducible, scalable research: an example with drake in R
Start: 2020-03-19T18:30:00-04:00
End: 2020-03-19T20:00:00-04:00
Location: Virtual Mtg

We all start out using things like Excel to analyze data. Sometimes we progress to entering commands in languages like R and python, then save our commands into a script and run that. However, if steps of that script take a long time to run, it can be hard to change things, as we know it will necessitate another long run. Life can also get complex as we get more complex data and more steps. Drake is a fairly new package in R, supported by rOpenSci, that streamlines this process. You connect together simple functions and create a plan, similar to running a script, but if any of the data or functions change, you can rerun it and it will automatically only rerun the changed portions. It can even run tasks in parallel (using other functions). The goal of this is a gentle introduction to why this is useful and how it works -- even if you do not know R, you should get the basic idea of creating an organized, readable workflow.

Please note: To do our part to prevent the spread of the COVID-19 virus, this meetup will be held Online, and a Zoom link to be sent to all attendees 30 minutes prior to the start of the Meetup.

This meetup will be hosted by Dr. Brian O'Meara, Professor and Associate Head, Ecology and Evolutionary Biology Department, University of Tennessee, Knoxville

Joshua Rosenberg

Alex Pawlowski

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Reproducible, scalable research: an example with drake in R

Virtual Mtg

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Reproducible, scalable research: an example with drake in R

KnoxData - a PyData group

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