Open Science and Reproducibility in R

by Monica Granados

Project Details

  • Language : English
  • Material required : R and RStudio
  • Instructed : R Symposium 2017
  • Contributed by : Monica Granados

Open Science and Reproducibility in R

Imagine if every paper you ever publish from now on could be reproduced by anyone around the world. Or a platform that gives you the power to integrate new data seamlessly into a manuscript complete with text and figures. In this workshop, we will be covering how to work in the open using R, R Markdown and GitHub. These three open platforms allow us to host data, analyze, visualize and produce a manuscript in one reproducible workflow. You will learn how to set up a repository in GitHub and manage branches, draw data from GitHub into R, write an R Markdown script for your manuscript and how to upload the R Markdown script into GitHub for reproducibility. The advantages of open, reproducible science are many. When working collaboratively, reproducible workflows allow collaborators to contribute simultaneously to the project with version control to preserve different iterations of the project. Working in the open also allows you share your research more widely, facilitating collaborative opportunities. At the end of the workshop we will also discuss the wider movement of open science, how it is helping breakdown economic barriers in science and education and how you can contribute.

Workshop material

  • The workshop material can be accessed here.