Welcome to EarthCube Interactive Workshops!
These short courses will teach you how to conduct reproducible research using Data Sciences tools. You will be working with R Markdown, Docker containerization, and Git for version control.
After these modules, you will be able to process your own research in a format suitable for analysis, writing your own analysis functions, and deriving data-driven insights via RMarkdown files and Jupyter Notebooks.
Module 1: Intro to Jupyter Notebooks
In this module, you will learn how to write your own Jupyter Notebook. In Module 2 you will also learn how to install dependencies and configure your conda environment. In Module 4 we will talk more in detail about what a Binder entails.
Module 2: Setting up your working environment with conda
This module will teach you how to organize your environments using conda
Module 3: Intro to GitHub
This module will teach you about Version Control and how to use Git and Github.
Module 4: Introduction to Binder
This module will teach you how to use the Binder properly guaranteeing reproducibility of your notebooks and repositories.
Module 5: Working with RMarkdown
In this module you will create, edit and run reproducible R code documents using RMarkdown.
Module 6: Introduction to Docker
This module will teach you about Docker and containerization. You will be able to launch third party containers and write your own Dockerfile.
Module 7: Development best-practices including FAIR data principles
This module will teach you different aspects in regards to Data Workflows, handling filenames and best practices such as testing, continuous integration and licensing.
References and Resources
Here are scripts to re-use and links to additional references and topics to learn.