# DUST 2026: Open Science Training > Three 50-minute lessons on open science, research data management, and the ethics of artificial intelligence for NIEHS Superfund Research Program trainees at the University of Arizona DUST Center, the UNM METALS Center, and the Texas A&M Superfund Research Center. The source repository is an Open Knowledge Format (OKF v0.2) bundle: every page carries YAML frontmatter with type, provenance (generated/sources), and lifecycle (status/stale_after) fields. Every page below is listed with three addresses that all return the same content: the rendered HTML page, its Markdown twin (page URL + `index.md`, served as text/markdown with the OKF frontmatter), and the raw source file on GitHub. Fetch whichever your tool is allowed to reach; many sandboxes permit github.com and raw.githubusercontent.com but not *.github.io. ``` Site page https://unm-carc.github.io/dust-2026// Markdown twin https://unm-carc.github.io/dust-2026//index.md Raw source https://raw.githubusercontent.com/UNM-CARC/dust-2026/main/docs/.md (branch main; a moving target) Content page /lessons/01-open-science/ -> https://raw.githubusercontent.com/UNM-CARC/dust-2026/main/docs/lessons/01-open-science.md Section listing /lessons/ -> https://raw.githubusercontent.com/UNM-CARC/dust-2026/main/docs/lessons/index.md ``` ## Lessons - [Lesson 1: Foundations of Open Science](https://unm-carc.github.io/dust-2026/lessons/01-open-science/): A 50-minute in-person lecture: what open science is, its six pillars, the nine Gold Standard Science tenets, and the 2026 public-access and publication-cost rules, with Superfund examples from Arizona and New Mexico. Markdown twin: https://unm-carc.github.io/dust-2026/lessons/01-open-science/index.md Raw source: https://raw.githubusercontent.com/UNM-CARC/dust-2026/main/docs/lessons/01-open-science.md - [Lesson 1 homework: Open Science, self-paced](https://unm-carc.github.io/dust-2026/lessons/01-open-science-self-paced/): The self-paced companion to Lesson 1: twelve modules with checkpoints on the six pillars, Gold Standard Science in depth, the 2026 public-access and publication-cost landscape, a full self-assessment, and the complete quiz. Markdown twin: https://unm-carc.github.io/dust-2026/lessons/01-open-science-self-paced/index.md Raw source: https://raw.githubusercontent.com/UNM-CARC/dust-2026/main/docs/lessons/01-open-science-self-paced.md - [Lesson 2: Modern Data Management](https://unm-carc.github.io/dust-2026/lessons/02-data-management/): A 50-minute in-person lecture: the data life cycle, FAIR and CARE, the 2026 NIH and NSF data management and sharing plan formats, repositories and licenses, and a two-site metal-mixture plan exercise, with Superfund examples from Arizona and New Mexico. Markdown twin: https://unm-carc.github.io/dust-2026/lessons/02-data-management/index.md Raw source: https://raw.githubusercontent.com/UNM-CARC/dust-2026/main/docs/lessons/02-data-management.md - [Lesson 2 homework: Data Management, self-paced](https://unm-carc.github.io/dust-2026/lessons/02-data-management-self-paced/): The self-paced companion to Lesson 2: twelve modules with checkpoints on the data life cycle, data rescue, metadata, repositories, FAIR and CARE, the 2026 NIH and NSF plan formats, licenses, three self-assessments, a two-site metal-mixture plan scenario, and the complete quiz. Markdown twin: https://unm-carc.github.io/dust-2026/lessons/02-data-management-self-paced/index.md Raw source: https://raw.githubusercontent.com/UNM-CARC/dust-2026/main/docs/lessons/02-data-management-self-paced.md - [Lesson 3: Ethics and Artificial Intelligence](https://unm-carc.github.io/dust-2026/lessons/03-ai-ethics/): A 50-minute in-person lecture: where AI bias comes from, the NIH, NSF, and journal rules that bind you, what never goes into a consumer AI, what changes when an agent can act, and two discussion scenarios, with Superfund examples from Arizona and New Mexico. Markdown twin: https://unm-carc.github.io/dust-2026/lessons/03-ai-ethics/index.md Raw source: https://raw.githubusercontent.com/UNM-CARC/dust-2026/main/docs/lessons/03-ai-ethics.md - [Lesson 3 homework: AI Ethics, self-paced](https://unm-carc.github.io/dust-2026/lessons/03-ai-ethics-self-paced/): The self-paced companion to Lesson 3: twelve modules with checkpoints on AI bias and mitigation, the NIH misconduct and application rules, journal disclosure and peer review, privacy and account types, energy and water, agentic AI, the September 2026 regulatory landscape, six discussion scenarios, the ethical AI checklist, and the complete quiz. Markdown twin: https://unm-carc.github.io/dust-2026/lessons/03-ai-ethics-self-paced/index.md Raw source: https://raw.githubusercontent.com/UNM-CARC/dust-2026/main/docs/lessons/03-ai-ethics-self-paced.md ## About - [About this training](https://unm-carc.github.io/dust-2026/about/training/): Who this training is for, why open science matters for Superfund research, how to use the lessons, technical implementation, and version history. Markdown twin: https://unm-carc.github.io/dust-2026/about/training/index.md Raw source: https://raw.githubusercontent.com/UNM-CARC/dust-2026/main/docs/about/training.md - [Additional resources](https://unm-carc.github.io/dust-2026/about/resources/): Curated links for open science, data management, Indigenous data governance, AI ethics, publishing, reproducibility, and staying current. Markdown twin: https://unm-carc.github.io/dust-2026/about/resources/index.md Raw source: https://raw.githubusercontent.com/UNM-CARC/dust-2026/main/docs/about/resources.md - [Credits and attribution](https://unm-carc.github.io/dust-2026/about/credits/): Source materials, contributors, institutional support, license, and how to cite DUST 2026. Markdown twin: https://unm-carc.github.io/dust-2026/about/credits/index.md Raw source: https://raw.githubusercontent.com/UNM-CARC/dust-2026/main/docs/about/credits.md - [Learn with an AI tutor](https://unm-carc.github.io/dust-2026/about/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. Markdown twin: https://unm-carc.github.io/dust-2026/about/ai-tutor/index.md Raw source: https://raw.githubusercontent.com/UNM-CARC/dust-2026/main/docs/about/ai-tutor.md - [Accessibility](https://unm-carc.github.io/dust-2026/about/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. Markdown twin: https://unm-carc.github.io/dust-2026/about/accessibility/index.md Raw source: https://raw.githubusercontent.com/UNM-CARC/dust-2026/main/docs/about/accessibility.md - [For AI agents](https://unm-carc.github.io/dust-2026/about/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. Markdown twin: https://unm-carc.github.io/dust-2026/about/ai-agents/index.md Raw source: https://raw.githubusercontent.com/UNM-CARC/dust-2026/main/docs/about/ai-agents.md ## Meta - [Full corpus in one file](https://unm-carc.github.io/dust-2026/llms-full.txt): every page's Markdown with frontmatter, links made absolute; about 330 KB, roughly 85,000 tokens. Prefer it over fetching pages one at a time. - [Documentation update log](https://unm-carc.github.io/dust-2026/log/): dated history of changes to this bundle. - [For AI agents](https://unm-carc.github.io/dust-2026/about/ai-agents/): endpoints, trust signals, and how to teach a lesson; includes what to do if you cannot fetch this site. - [Learn with an AI tutor](https://unm-carc.github.io/dust-2026/about/ai-tutor/): learner-facing prompts for lecture, tutor, and interactive modes. - [Accessibility](https://unm-carc.github.io/dust-2026/about/accessibility/): accessibility statement and the per-lesson accessibility profile. - [Sitemap](https://unm-carc.github.io/dust-2026/sitemap.xml) and [robots.txt](https://unm-carc.github.io/dust-2026/robots.txt). - [Source repository](https://github.com/UNM-CARC/dust-2026): the bundle itself; `docs/` mirrors the site paths one to one.