Overview:

Reproducible Science is a project that provides a boilerplate for reproducible and transparent scientific work. It follows the philosophy of Cookiecutter Data Science, aiming to provide a standardized yet flexible project structure for conducting and sharing data science work.

Features:

Reproducibility: Provides a framework that promotes reproducibility in scientific work.
Transparency: Focuses on transparency by providing a clear project structure for organizing data science work.
Flexibility: Allows for customization according to specific project requirements.
Standardization: Encourages a logical and standardized approach to data science projects.
Easy Installation: Can be easily installed using the pip command line.

Usage:

To start a new science project using Reproducible Science, you can use the following command:

cookiecutter gh:mkrapp/cookiecutter-reproducible-science

Summary:

Reproducible Science is a project that aims to promote reproducibility and transparency in scientific work. It provides a standardized project structure while allowing flexibility for customization. By following the philosophy of Cookiecutter Data Science, Reproducible Science offers a logical and standardized approach to data science projects. It is easily installable using the cookiecutter command line tool.

Mkrapp

Cookiecutter Reproducible Science