IDI

IDI

@institutional.org

A research center at Harvard working to strengthen society’s connection to knowledge by advancing our access to and understanding of the data that shapes AI.

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

Enriched Text contains 217B tokens from 983K @harvardlibrary.bsky.social volumes, organized into 1.39B annotated paragraphs across 250 languages. Researchers can use the dataset to analyze language, repeated passages, line breaks, and paragraph predictability.

Visual Elements extends the dataset to images embedded in scanned pages, producing 22.6M visual elements – including illustrations, photographs, charts, musical notation, and decorative materials – linked to their source volumes and pages.

When a newspaper becomes a wall of OCR text, columns collapse, headlines mix with ads, and reading order disappears. The Institutional Data Initiative (@institutional.org) and Boston Public Library (@bpl.boston.gov) built a pipeline and dataset to make historical newspapers more accessible.🧵

institutional.orgMaking 1.47 Million Historical Newspaper Pages Available as High-Quality, Granular Data | IDIThe Institutional Data Initiative at the Harvard Law School Library and Boston Public Library release an open dataset and processing pipeline that make historical newspapers more accessible for resear...
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The dataset supports more than keyword search: you can follow reading order, identify people and places, and examine how newspaper design and advertising changed across time. Institutional Newspapers includes the dataset, models, and an open-source processing pipeline:

institutional.orgMaking 1.47 Million Historical Newspaper Pages Available as High-Quality, Granular Data | IDIThe Institutional Data Initiative at the Harvard Law School Library and Boston Public Library release an open dataset and processing pipeline that make historical newspapers more accessible for resear...

The Institutional Data Initiative at the @hls.harvard.edu Library works with knowledge institutions to increase the availability, diversity, and responsible use of training data for AI. Reach out and join us.

When a newspaper becomes a wall of OCR text, columns collapse, headlines mix with ads, and reading order disappears. The Institutional Data Initiative (@institutional.org) and Boston Public Library (@bpl.boston.gov) built a pipeline and dataset to make historical newspapers more accessible.🧵

institutional.orgMaking 1.47 Million Historical Newspaper Pages Available as High-Quality, Granular Data | IDIThe Institutional Data Initiative at the Harvard Law School Library and Boston Public Library release an open dataset and processing pipeline that make historical newspapers more accessible for resear...

Institutional Newspapers contains 1.47 million pages from the Boston Public Library’s collections, representing 16.3 billion tokens and a multilingual record of Boston’s communities across 73 languages.

Instead of treating each page as one image, our pipeline divides it into individual crops. Those crops are processed as articles, advertisements, photographs, cartoons, headings, mastheads, or empty space, with OCR tailored to each segment.

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When libraries join Google Books, Google not only scans their books, it also makes a wealth of image, OCR, & metadata available to them via the Google Return Interface (GRIN). But working with GRIN can be challenging, so we're releasing a tool to make it easier. www.institutional.org/posts/grin-t...

institutional.orgAnnouncing the release of GRIN TransferGRIN Transfer, an open source tool that allows Google Books partner libraries to more easily access their Google Books collection.

Join us tomorrow at 10AM EST: tinyurl.com/y3ye6cz6

tinyurl.comWelcome! You are invited to join a meeting: IDI Talk with Michele Dolfi & Peter Staar on SmolDocling. After registering, you will receive a confirmation email about joining the meeting.Please join us for a talk with Michele Dolfi & Peter Staar from IBM Research in Zurich to discuss their work on SmolDocling, an “ultra-compact” model for diverse OCR tasks.
IDI@institutional.org

Can a small visual language model read documents as effectively as models 27 times its size? Next Friday, IDI will host Michele Dolfi and Peter Staar from IBM Research Zurich to discuss their work on SmolDocling, an “ultra-compact” model for diverse OCR tasks.

Can a small visual language model read documents as effectively as models 27 times its size? Next Friday, IDI will host Michele Dolfi and Peter Staar from IBM Research Zurich to discuss their work on SmolDocling, an “ultra-compact” model for diverse OCR tasks.

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This Monday, @institutionaldatainitiative.org will host Petr Knoth 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.

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Today we released Institutional Books 1.0, a 242B token dataset from Harvard Library's collections, refined for accuracy and usability. 🧵

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We look forward to growing Institutional Books through community. We welcome collaboration from researchers and model makers as we: - Evaluate the dataset’s impact on model outputs - Continuing to refine our OCR pipelines View the dataset on Hugging Face: huggingface.co/datasets/ins...

huggingface.coinstitutional/institutional-books-1.0 · Datasets at Hugging FaceWe’re on a journey to advance and democratize artificial intelligence through open source and open science.

We hope Institutional Books will be the beginning of a process that makes millions more books accessible to the public for a variety of uses. We welcome feedback as we continue to expand this dataset, refine its contents, and sharpen our process. www.institutionaldatainitiative.org/institutiona...

institutionaldatainitiative.orgInstitutional Books | Institutional Data InitiativeInstitutional Books 1.0 is our first release of public domain books. This set was originally digitized through Harvard Library’s participation in the Google Books project..

Today we released Institutional Books 1.0, a 242B token dataset from Harvard Library's collections, refined for accuracy and usability. 🧵

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We included extensive volume-level metadata with both original and generated components, such as results from text-level language detection.

As part of our refinement work, we supplemented the original OCR-extracted text with a post-processed version that utilizes line detection to reassemble the text according to the line type.

Today we released Institutional Books 1.0, a 242B token dataset from Harvard Library's collections, refined for accuracy and usability. 🧵

We analyzed the dataset’s coverage across time, topic, and language and found: - 40% of English text + long tail of 254 languages - 20 clear topical tranches - Largely published in the 19th and 20th centuries Technical report here: arxiv.org/abs/2506.08300

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The @institutionaldatainitiative.org is proud to support The New Commons challenge. $100k grants along with mentorship. Let's get impactful data into the AI ecosystem.

The GovLab@thegovlab.org

(1/4) CALL FOR APPLICATIONS FOR DATA COMMONS FOR AI 🏆Today, The Open Data Policy Lab (a collaboration btwn The GovLab & @microsoft.com launched The New Commons Challenge—an innovation challenge to foster the creation of data commons that can support generative AI developed in the public interest.

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