Scientists Who Code Example Repository

Building Open Environmental Infrastructure with Non-Developer Teams

This repository is a demo/model project for the Scientists Who Code pedagogy, showing how interdisciplinary teams (including researchers, students, and community members without formal programming training) can co-create open, reproducible environmental data science tools.

It’s designed for use in workshops, roundtables, and collaborative projects where participants have mixed programming skill levels and need clear examples of:

• GitHub workflows
• CyVerse & Jupyter Notebook integration
• Documentation best practices
• Ethical, open science principles

Purpose

Environmental science increasingly relies on code, yet many scientists and community members are not trained as software developers. This example repository provides:

• A safe, low-stakes space to practice collaborative coding and GitHub usage.
• A template structure for Earth and environmental data science projects.
• A teaching aid for project managers leading mixed-skill, interdisciplinary teams.

Repository Structure

Getting Started

1. Clone the repository git clone https://github.com/lijo8146/scientists_who_code_demo_repo/

   cd scientists-who-code-demo_repo

2. Set up the environment (Conda)

   conda env create -f environment.yml
   conda activate scientists-who-code

3. Open Jupyter Notebooks

   jupyter lab

Workshop Activities

This repository supports the following hands-on learning activities:

Basic GitHub Workflow

• Forking, cloning, branching, and pull requests.
• Jupyter Notebook Practice
• Open an existing notebook, run cells, and modify code.
• Adding New Data
• Place data in the /data folder, update documentation.
• Collaborative Documentation
• Edit README.md and create a CONTRIBUTING.md.

Ethical & Open Science Principles

This demo reinforces:

• Transparency — All code and data are open and documented.
• Inclusivity — Materials are accessible to participants with varying technical backgrounds.
• Reproducibility — Clear setup instructions ensure others can re-run analyses.
• Respect for Indigenous Data Sovereignty — Follow CARE Principles when using Tribal data.

Contributing

We welcome contributions from all skill levels. See CONTRIBUTING.md for guidelines on:

• Adding notebooks or scripts
• Improving documentation
• Suggesting new features

License

This repository is licensed under the MIT License.

Contact

For questions or collaboration opportunities, please contact: Lilly Jones lijo8146@colorado.edu