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Designing a Reproducible Workflow with R and GitHub
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0:00 - Introduction
3:18 - Learning Objectives
3:57 - Definitions: reproducibility / replicability
7:00 - Context for reproducible workflows
10:35 - Reproducibility spectrum
12:12 - Overview of an approach to practical reproducible workflows
17:59 - What is Version Control: Git & GitHub
45:25 - Hands on with RStudio, library(usethis) + git & GitHub
1:15:40 - Tips on reproducibility vis-a-via literate coding with R Markdown and RStudio
1:19:40 - Literate coding
1:21:13 - Relative file paths
1:27:00 - Archive your GitHub milestones (releases) to an archival repository (Zenodo, e.g.)
1:31:15 - Licenses, creative commons, or copyright
1:37:40 - Wrap-up, tips, Code Ocean
1:43:53 - Research Data Repository
The importance of reproducibility, replication, and transparency in the research endeavor is increasingly discussed in academia. This workshop will introduce foundational strategies that can increase the reproducibility of your work and present a potential end-to-end reproducible workflow using a suite of tools, including git, RStudio, Binder, and Zenodo. Configuration for the hands-on portion of the workshop will be sent to participants one week before the workshop. Participants are expected to bring their laptop already configured for the workshop.
Prerequisites:
* A GitHub account
Preparation Steps
1. Install and upgrade R and R Studio(!):
2. Sign up for a free GitHub account
In the video we
a. Create a github personal access token
b. set the git credentials on your local workstation
c. verify the credentials
d. create a new RStudio project and git repository in one step
e. Push the repository to GitHub by associating the local git remote with GitHub.
Note: git is known for it's exceptionally robust functionality combined with a widely acknowledged harsh user interface. In the workshop we will attempt to explain why so many people have decided to use this version control tool for its many affordances. Plan to learn just enough git to leverage basic version control reproducibility features.
3:18 - Learning Objectives
3:57 - Definitions: reproducibility / replicability
7:00 - Context for reproducible workflows
10:35 - Reproducibility spectrum
12:12 - Overview of an approach to practical reproducible workflows
17:59 - What is Version Control: Git & GitHub
45:25 - Hands on with RStudio, library(usethis) + git & GitHub
1:15:40 - Tips on reproducibility vis-a-via literate coding with R Markdown and RStudio
1:19:40 - Literate coding
1:21:13 - Relative file paths
1:27:00 - Archive your GitHub milestones (releases) to an archival repository (Zenodo, e.g.)
1:31:15 - Licenses, creative commons, or copyright
1:37:40 - Wrap-up, tips, Code Ocean
1:43:53 - Research Data Repository
The importance of reproducibility, replication, and transparency in the research endeavor is increasingly discussed in academia. This workshop will introduce foundational strategies that can increase the reproducibility of your work and present a potential end-to-end reproducible workflow using a suite of tools, including git, RStudio, Binder, and Zenodo. Configuration for the hands-on portion of the workshop will be sent to participants one week before the workshop. Participants are expected to bring their laptop already configured for the workshop.
Prerequisites:
* A GitHub account
Preparation Steps
1. Install and upgrade R and R Studio(!):
2. Sign up for a free GitHub account
In the video we
a. Create a github personal access token
b. set the git credentials on your local workstation
c. verify the credentials
d. create a new RStudio project and git repository in one step
e. Push the repository to GitHub by associating the local git remote with GitHub.
Note: git is known for it's exceptionally robust functionality combined with a widely acknowledged harsh user interface. In the workshop we will attempt to explain why so many people have decided to use this version control tool for its many affordances. Plan to learn just enough git to leverage basic version control reproducibility features.
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