Skip to content

Maka-Sitomniya

Welcome to the Maka-Sitomniya repository, part of the Environmental Data Science Innovation and Inclusion Lab (ESIIL). This repository serves as the central hub for our working group, hosting our project description, proposals, member bios, codebase, and more.

Our Project

The world is faced with growing threats from multiple, interacting environmental challenges ranging from chemical pollution to increasing demands and diminishing supplies of freshwater to loss of biodiversity to the climate crisis. Indigenous communities are particularly vulnerable to these threats as a result of a long history of injustice. At the same time, their holistic worldview, long tenure on the lands and waters and time-tested stewardship practices provide the local knowledge necessary to understand and respond to environmental challenges. What is lacking are the resources and technical expertise to combine Indigenous Knowledges with the latest advances in data collection and analysis.

Climate change vulnerability assessment, mitigation and adaptation all depend on timely and reliable data. Recent advances in remote sensing technology and environmental data science (EDS) provide powerful tools for planners and decision-makers, but only if the data and analyses are accessible to them. Our Working Group is not focused on specific technological advances, but on enabling Tribes to access and use EDS for their own purposes. Our Indigenous-led group, consisting predominantly of Indigenous scientists and Tribal College faculty, proposes to facilitate the adoption of EDS by creating a DataCube and workflow that are customizable for the needs of specific Tribes and useful for training to build Tribal capacity. Advancing EDS is not just about pushing the edges of the science, it must also be about expanding accessibility and use of the science to benefit society, and extending its reach into communities that would otherwise be excluded.

Project Proposal

[Link to the detailed project proposal document or include the proposal directly in the repository. This should outline the goals, methodologies, anticipated challenges, and projected timelines.]

Group Members

[List the names and a brief description of each group member, possibly linking to their personal or professional web pages.]

Code Repository

This section of the repository will include all the code developed for the project. You can structure it as follows:

  • Analysis Code: Scripts for data analysis, statistical modeling, etc.
  • Data Processing: Scripts for cleaning, merging, and managing datasets.
  • Visualization: Code for creating figures, charts, and interactive visualizations.

Meeting Notes and Agendas

Meeting notes and agendas will be regularly updated here to keep all group members informed and engaged with the progress and direction of the project.

Contributing to This Repository

We welcome contributions from all group members. To maintain the quality and integrity of the repository, please adhere to the following guidelines:

  • Make sure all commits have a clear and concise message.
  • Document any major changes or decisions in the meeting notes.
  • Review and merge changes through pull requests to ensure oversight.

Getting Help

If you encounter any issues or have questions about how to contribute, please refer to the ESIIL Support Page or contact the repository maintainers directly.

Customize Your Repository

As a new working group, you'll want to make this repository your own. Here's how to get started:

  1. Edit This Readme: Replace the placeholder content with information about your specific project. Ensure that the introduction, project overview, and objectives clearly reflect your group's research focus.

  2. Update Group Member Bios: Add details about each group member's expertise, role in the project, and professional background. Include links to personal or professional web pages to foster community engagement and collaboration.

  3. Organize Your Code: Structure your codebase in a way that is logical and accessible. Use directories and clear naming conventions to make it easy for all members to find and contribute to different parts of the project.

  4. Document Your Data: Include a data directory with README files explaining the datasets, sources, and any preprocessing steps. This will help new members understand and work with the project's data effectively.

  5. Outline Your Methods: Create a detailed METHODS.md file where you describe the methodologies, software, and tools you will be using in your research. This transparency will support reproducibility and collaborative development.

  6. Set Up Project Management: Utilize the 'Issues' and 'Projects' features on GitHub to track tasks, discuss ideas, and manage your workflow. This can help in maintaining a clear view of progress and priorities.

  7. Add a License: Choose and include an appropriate open-source license for your project, ensuring that the broader community understands how they can use and contribute to your work.

  8. Create Contribution Guidelines: Establish a CONTRIBUTING.md file with instructions for members on how to propose changes, submit issues, and contribute code.

  9. Review and Merge Workflow: Decide on a workflow for reviewing and merging changes. Will you use branch protection? Who will have merge privileges? Document this process to avoid confusion.

  10. Establish Communication Channels: Beyond GitHub, set up additional communication channels like Slack, Discord, or email lists for quick and informal discussions.

Remember, the goal is to make your repository clear, accessible, and useful for all current and future members of your working group. Happy researching!

Last update: 2024-07-02