AI enables new forms of research, but only where information is computationally accessible. Today, IDI (@instdin) and the University of Michigan Library (@UMichLibrary) are releasing a structured dataset that makes 186 years of U-M’s Board of Regents Proceedings newly accessible. Links in the thread below. Organizational decision-making is fertile ground for AI-assisted research, but board minutes often bury key decisions in narrative prose. Using reasoning models, we worked with U-M Library to extract and structure these decisions so researchers can use computational tools to study the evolution of U-M. Across nearly two centuries, we identified leadership changes, fundraising progress, building campaigns, and other strategic plans. These include the creation of university race and gender policies following the passage of the Civil Rights Act as well as a 1921 $1M alumnae drive for a “women’s building,” launched after women were barred from entering the Michigan Union without a male escort. This project is the first of many that the Institutional Data Initiative at Harvard Law School Library is undertaking to help libraries and other knowledge institutions enable computational access to their collections. If you represent a library and would like to work together, we'd love to hear from you.

Amazing work from an amazing team using @instdin’s Institutional Books data release. Their dedication to detail and accuracy is sorely missing from the vast majority of historical-data work from the AI community. Yet there’s so much work to be done and benefit to getting it right

Even if you're not a partner library, you might be curious about what it's like to work with GRIN. Our technical report has a wealth of details: arxiv.org/abs/2511.11447

We're also sharing the pipeline we developed for Institutional Books that seamlessly dedupes, classifies, and enhances the data once GRIN Transfer brings it down. institutional.org/tools

When libraries participate in Google Books, Google not only scans their books, it also makes a wealth of image, OCR, and metadata available to them via the Google Return Interface (GRIN). But working with GRIN can be challenging.

This Monday, @instdin will host @petrknoth to share his experience leading CORE ("The world’s largest collection of open access research papers") as the rise of AI brings new meaning, and challenges, to stewarding knowledge repositories. Join us virtually via the link below.

Tomorrow, it's our pleasure to host @ayahbdeir to talk about the power of data in building an AI ecosystem that's open, transparent, and fair. 11am ET on June 17th. Register at the link below to attend virtually. Cohosted by the @instdin and @BKCHarvard.

As the Institutional Data Initiative (@instdin) expands its mission, we’re announcing a collaboration with the Boston Public Library (@BPLBoston) to develop AI-driven tools capable of accelerating new digitization at libraries across the world, starting at BPL. 🧵

I'm pleased to announce we're expanding our mission at the Institutional Data Initiative (@instdin) with an open call for institutional collaborators, new digitization at Harvard Law School Library, and additional support to advance this work.

Today we're launching the Institutional Data Initiative to work with libraries, gov agencies, and other knowledge institutions to help refine and publish their collections as data, with an eye toward AI. 🧵