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About this site

Who the training is for, where its material came from, how to learn it with an AI tutor, its accessibility features, how AI agents should read it, and what has changed.

  • About this training - Who this training is for, why open science matters for Superfund research, how to use the lessons, technical implementation, and version history.
  • Additional resources - Curated links for open science, data management, Indigenous data governance, AI ethics, publishing, reproducibility, and staying current.
  • Credits and attribution - Source materials, contributors, institutional support, license, and how to cite DUST 2026.
  • Learn with an AI tutor - How to load a DUST 2026 lesson into Claude, ChatGPT, Gemini, or NotebookLM and take it as a lecture, a Socratic tutorial, or an interactive quiz, with prompts for screen-reader users, deaf learners, and learners whose first language is not English.
  • Accessibility - Accessibility statement for DUST 2026: what the site provides for screen-reader users, deaf and hard-of-hearing learners, and learners whose first language is not English, how to use it with AI assistants, known limitations, and how to report a barrier.

  • For AI agents - How agents and harnesses should consume this site: llms.txt, per-page Markdown with OKF frontmatter, trust signals, and how to teach a lesson in lecture, tutor, or interactive mode while honoring its accessibility profile.

  • Update log - Chronological history of changes to this training bundle.

Machine-readable versions of this page: Markdown twin · raw source on GitHub · llms.txt · llms-full.txt (whole site). See For AI agents.