Reproducibility and collaboration when your data is really large or confidential

doi:10.17605/OSF.IO/59MKJ

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[![License: CC BY-NC 4.0](https://licensebuttons.net/l/by-nc/4.0/80x15.png)](https://creativecommons.org/licenses/by-nc/4.0/) Many new collaborative and often reproducible or dynamic tools are being developed or in use. One feature that they have in common is that is hard to use them when the data being used is really large (you cannot put 1TB of data into Github) or confidential (don’t even try to do that with Github). In this workshop, I will convey some tips and tricks on how to set up a reproducible environment that allows for such features of the data. ## Materials - [slides](https://osf.io/pjq8v/) - [Rmarkdown demo](https://osf.io/j4vbe/) ([HTML version](https://labordynamicsinstitute.github.io/day-of-data-2021/safe-and-efficient.html)) - [Rstudio version](https://rstudio.cloud/project/2121664) (requires account on rstudio.cloud, Github, Google, may not be permanent)

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