







Integrating open and reproducible science into higher education
Introduction to Open Science
This course introduces the principles and practices of open science, with an emphasis on reproducible research workflows, transparent reporting, and collaborative scholarship. Students will critically examine reproducibility, explore tools that support openness (such as Git, GitHub, and Quarto), and apply these tools in hands-on assignments and a final open project. Students will also explore how open science practices vary across disciplines, including education, humanities, social sciences, industry and government, and STEM contexts. This course emphasizes applying open science principles to real-world data problems in alignment with the principles of producing reproducible research.
Center for Open Science
At the Center for Open Science, our mission is to increase openness, integrity, and reproducibility of scholarly research. Promoting these practices within the research funding and publishing communities accelerates scientific progress

Reproducible research: methodological principles for transparent…
This Mooc proposes methodological principles for open and transparent science. It deals in a practical way with note-taking, computational documentation, replicability of analyses.
Improving scientific mentorship with "Open Labs" — science better
Open Labs would be a place for experienced scientists to post their open questions and curiosities — a list of the ideas they don't have time to pursue personally but wish someone would.

The Minimum Viable Scientific Record
The open science movement does not lack a shared vision. Decades of declarations, statements of principle, and calls to action have failed to put that vision into practice. This essay proposes a minimum viable scientific record (MVR) that would make the open science vision possible, and asks funders to make operating on it a condition of their money.


DR Tulu: An open, end-to-end training recipe for long-form deep research | Ai2
We introduce Deep Research Tulu (DR Tulu), an open post-training recipe and framework for long-form deep research agents.
