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. www.institutional.org/tools

That's why we built GRIN Transfer: a tool for downloading collections, big or small. GRIN Transfer handles request batching, failure recovery, and data aggregation so that libraries can focus on using the data rather than simply gaining access to it. www.institutional.org/posts/grin-t...

We learned this lesson over the months it took to download 1M of Harvard Library's books for our Institutional Books release. As a result, many libraries have yet to take full advantage of the wonderful resources GRIN provides.

June 23rd at 12:45pm ET. RSVP here: harvard.zoom.us/meeting/regi...

Cohosted by @institutionaldatainitiative.org and The Berkman Klein Center. harvard.zoom.us/webinar/regi...

The @institutionaldatainitiative.org at Harvard works with knowledge institutions to increase the availability, diversity, and responsible use of training data for AI. Reach out and join us.

Our goal is to develop methods and tools that can support expert staff at libraries everywhere, increasing the breadth of materials that can be digitized and the speed at which they’re made accessible to the public. Learn more at BPL: www.bpl.org/news/boston-...

Together, we’ll research opportunities to generate machine-readable representations of items, add searchable metadata, and begin the structuring of entire collections—all at the moment each item leaves the imaging station.

IDI and BPL are working to change this by collaborating at the outset of a large digitization project, exploring how AI might complement human expertise and strengthen the process in its earliest stages.

BPL is embarking on a new initiative to digitize hundreds of thousands of historic items. Conventional approaches to this scale lead to an impossible choice: sacrifice depth for breadth or drastically limit what gets digitized. AI tools can help, but they’re relegated to the end of the process.

With our digitization at Harvard Law School Library, we'll work to increase access to unique collections, such as the Supreme Court Records and Briefs that are critical to understanding decision-making at the highest U.S. court yet remain largely inaccessible.

If you're part of a library, university, or other knowledge institution and interested in working with a team of data scientists to refine and publish your data, we'd love to chat. And if you're a data scientist or community builder interested in working with institutions, we're hiring.

IDI is building a collection of large, impactful, and widely available datasets to increase AI’s accessibility and diversity while reaffirming institutions as stewards of knowledge.