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Project Team

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Image Analysis for Archival Discovery (Aida)

The Aida research team explores applications of image analysis and machine learning in digital libraries of historic materials. We’re especially interested in what we might learn from the millions of digital images that librarians, archivists, and others are creating as they digitize the cultural record. We’re intrigued by the questions that machine learning approaches might help to surface in these collections and about our professional practices—and also by the questions our collections and professional practices might help to surface about machine learning.

Our current and recent efforts include “Digital Libraries, Intelligent Data Analytics, and Augmented Description: A Demonstration Project” (Library of Congress), “Extending Image Analysis for Archival Discovery” (IMLS, LG‐71‐16‐0152‐16), and “Oceanic Exchanges: Tracing Global Information Networks In Historical Newspaper Repositories, 1840-1914” (subaward on IMLS, LG-00-17-0104-17).

Code & Data

Code developed for our project is available via our GitHub organization page. See also the Exploring-ML-with-Project-Aida repository distributed by the Library of Congress.

Data generated for our project are made available through appropriate data repositories designed for long-term storage, preservation, and access. See our project page on the Open Science Framework:

Documents, Publications, Presentations

News & Updates