Skip to content

Self-paced tutorials that review key data literacy concepts and data analysis skills. Published materials can be found at:

License

Notifications You must be signed in to change notification settings

maxwell-burner/NEON-Data-Skills

 
 

Repository files navigation

Welcome to the NEON Data Skills GitHub Repo!

NEON Data Skills provides tutorials and resources for working with scientific data, including that collected by the National Ecological Observatory Network (NEON). NEON is an ecological observatory that will collect and provide open data for 30 years.

For more information on NEON, visit the website: www.neonscience.org

This repo contains the materials used to build the NEON Data Skills resources that are available for use on the NEON Data Skills section of the NEON website.

Usage

Contributing

If you would like to make a change to one of the resources, please fork the repo and make a pull request to the master branch with the suggested change. All pull requests are reviewed for scientific accuracy and educational pedagogy. Individuals who make significant contributions can request to be listed as contributors on individual tutorials.

Please start by copying the template (/tutorials-in-development/tutorialTemplate.md) if you are creating a new tutorial.

Questions?

Having a problem getting something to work or want to know why the repo is setup in a certain way? Email us neondataskills -AT- BattelleEcology.org or file a GitHub Issue.

License

GNU AFFERO GENERAL PUBLIC LICENSE Version 3, 19 November 2007

Disclaimer

The National Ecological Observatory Network is a major facility fully funded by the National Science Foundation. Any opinions, findings, and conclusions or recommendations expressed in this material do not necessarily reflect the views of the National Science Foundation.

Information and documents contained within this repository are available as-is. Code or documents, or their use, may not be supported or maintained under any program or service and may not be compatible with data currently available from the NEON Data Portal.

About

Self-paced tutorials that review key data literacy concepts and data analysis skills. Published materials can be found at:

Resources

License

Stars

Watchers

Forks

Packages

No packages published

Languages

  • Jupyter Notebook 61.9%
  • HTML 36.3%
  • R 1.5%
  • Python 0.3%