Welcome to LeapFROGS - A platform for FAIR science practice and publishing

Sharing research data, software, and workflow is fundamental to building a Findable, Accessible, Interoperable, and Reusable (FAIR) open science ecosystem. Indeed, over the past decade, funders and publishers have introduced open science policies emphasizing reproducibility, recognizing increased frameworks that support the sharing of reproducible science products.

LeapFROGS is a free online platofrm that curates lecture materials on science practice and publishing, along with interactive, self-graded exercises to create self-paced learning modules on various aspects of scienctific research. After you have completed these modules, you will be able to use Python and R more effectively for your research and publish all artifacts of your research according to FAIR principles.

This page runs on a python3 kernel.

Module 1: Introduction to Python

In this module, you will learn how to write basic Python code. Make sure that you go through the material provided in the links before attempting the exercises. You have two solutions to attempt the exercise (1) Write directly into the console and click `run code`. You will be told whether your get the correct answer. If stuck, you can ask for a hint or show the solution. Note that the first time you do this, a cloud server will be set up and it may take some time. Also do not navigate away from the code block (e.g., by opening another exercise) as this will stop the execution. (2) Attempt this on your local machine and use the Show solution tab to verify that you did the exercise correctly. You can also use the hints to help you if you choose to run locally.

Module 2: The scientific Python Stack

Now that you have learned about basic Python; let's talk about the scientific Python stack, which contains the functionalities that you will most likely need.

Module 3: Timeseries analysis

Write about what is done in this module.

Module 4: Principles of FAIR Scientific Publishing

This module provides fundamental principles in scientific publishing to ensure that all artifacts of science are Findable, Reproducible, Interoperable, and Reusable (FAIR). [Link to full slide deck]

About this course

This is a free, open source course on how to use different Data Science Techniques and Tools to make your science FAIR. It is made possible by a grant from the National Science Foundation RISE2324732. Contributions and comments on how to improve the course are welcome! To file an issue go to: https://github.com/LinkedEarth/LeapFROGS/issues

About me

The sharing of open source data, code, and workflows is fundamental to the building of a FAIR (Findable, Accessible, Interoperable, and Reusable) research ecosystem. Open source tools allow for a community to come together and contribute to the development and improvement of research infrastructure. Such collaborations lead to more robust and efficient solutions, as well as increased transparency and accessibility.The geoscience community is only now beginning to harness the power of the open source model, and formal training on the benefits and proper use of this model is still missing from most geoscience curricula. While computer science courses may provide some level of training, the technical details often do not align with the specific needs of geoscientists. Our objective is to build human infrastructure to promote reproducible and transparent geoscience by educating geoscientists on the effective utilization of open source resources through practical applications in their own scientific research.