Introducing LeapFROGS: a platform for open science practice and publishing
TL;DR: LeapFROGS, with a kernel in Python and in R, is an asynchronous platform for learning these open-source languages for scientific applications and time series analysis and for sharing your science to make it open and reproducible. The platform supports asynchronous learning activities as well as training workshops.
As announced last Fall, the latest LinkedEarth endeavor consists of synchronous and synchronous training activities in the area of open geoscientific research and publishing. This blog post offers an overview of the asynchronous platform: LeapFROGS (Python and R).
Why FROGS?
Sharing research data, software, and workflows is fundamental to building a Findable, Accessible, Interoperable, and Reusable (FAIR) open science ecosystem. Indeed, over the past decade, funders and publishers alike have introduced open science policies emphasizing reproducibility, recognizing increased frameworks that support the sharing of reproducible science products. The next logical step is to train the community in the use of these frameworks while they work on their scientific problems.
FROGS is also a nod to the national origin of half of the instructors.
LeapFROGS
The goal of LeapFROGS is to offer a platform for asynchronous learning of Python, R, time series analysis, and open science publishing. The platform contains a mix of short text introduction to a topic with links to relevant resources to learn more about the subject, coding exercises and multiple choice questions to test understanding of the subject matter. As of July 2024, the platform contains the following modules:
- Introduction to Python or R. This module focuses on a basic introduction to programming for these two languages from common data types to loops and conditionals. The modules also touch upon writing functions.
2. Python/R for scientific applications. The second module covers the use of Python/R in science. For Python, the module covers the basics of the scientific Python stack, including libraries such as NumPy, Pandas, Matplotlib for visualization and Cartopy for mapping among other useful resources for scientists working in Python. For R, the module covers R Data Frames and useful packages from tidyverse such as dplyr, tidyr, tibble, and ggplot2.
3. Timeseries analysis. The module covers data processing for timeseries analysis, measure of association, the use of surrogates for hypothesis testing, and spectral and wavelet analysis. The lectures associated with this module can be accessed on Figshare. Exercises can be accessed here for Python and here for R. LeapFROGS also contain multiple choice quizzes to assess understanding of the material.
4. The Scientific Paper of the Future. This module provides fundamental principles in open scientific publishing and walks through best practices on how to share data, software, and workflow. It is based on the original scientific of the paper materials put together by Yolanda Gil and colleagues and updated for new technologies such as Binder that support open science. The new materials are available on Figshare and summarized on LeapFROGS with quizzes to test understanding of the materials.
5. Introduction to Github. This module provides an introduction to the GitHub platform to share research and collaborate.
Who is LeapFROGS for?
Anyone can use this platform and we hope it will become a resource for a community of scientists using Python and/or R for their analyses, are interested in open science and making their research products reproducible and FAIR.
So far, LeapFROGS has supported a in-person hackathon (PyRATES) event for 18 geoscientists.
