Conservation biologists today work with large and disparate datasets to monitor and study species and habitats. However, it is imperative that practitioners and academics are trained in organizing, managing and analyzing such large datasets using reproducible tools and techniques. The goals of this workshop are to provide participants with: (1) Best practices for organizing and managing ecological datasets; (2) Introduction to version control and GitHub and (3) Best practices for writing reproducible code using R & Git. At the end of this workshop, participants should be able to cultivate and derive reproducible pipelines for handling different sets of data and obtain an introductory understanding of version control using GitHub and R.
(given that the entire description is less than 300 words, I have copy-pasted the same twice to meet the portal's demands)
Conservation biologists today work with large and disparate datasets to monitor and study species and habitats. However, it is imperative that practitioners and academics are trained in organizing, managing and analyzing such large datasets using reproducible tools and techniques. The goals of this workshop are to provide participants with: (1) Best practices for organizing and managing ecological datasets; (2) Introduction to version control and GitHub and (3) Best practices for writing reproducible code using R & Git. At the end of this workshop, participants should be able to cultivate and derive reproducible pipelines for handling different sets of data and obtain an introductory understanding of version control using GitHub and R.
Conservation biologists today work with large and disparate datasets to monitor and study species and habitats. However, it is imperative that practitioners and academics are trained in organizing, managing and analyzing such large datasets using reproducible tools and techniques. The goals of this workshop are to provide participants with: (1) Best practices for organizing and managing ecological datasets; (2) Introduction to version control and GitHub and (3) Best practices for writing reproducible code using R & Git. At the end of this workshop, participants should be able to cultivate and derive reproducible pipelines for handling different sets of data and obtain an introductory understanding of version control using GitHub and R.
The first part of the workshop will focus on the necessity for reproducible approaches in conservation biology, followed by an introduction to data management, organization, and file naming conventions.
The second half of the workshop will be focused on version control, GitHub and using it with RStudio.
Towards the end, we will go over useful resources and functionality from packages that are commonly used.
Specific instructions for attendees will be provided in an email once they register. Pre-workshop instructions Please bring your own device, preferably with RStudio installed. Create a account on GitHub - it's free!. Please note that when you are creating a GitHub account for the first time, I would recommend that you do not click the 'Continue with Google' option and instead manually enter your email address, set a password and username. Else, if you used one of your gmail addresses automatically, please ensure that you set a password for your account. Download and install Git.
