The Library’s Digital Innovation Labs Section “has undertaken a range of programs aimed at maximizing the use of digital collections and supporting emerging research methods,” including using machine learning and crowdsourcing prototypes, according to a solicitation posted Tuesday to beta.SAM.gov. “Now, the Library of Congress seeks to build on these initial experiments to further examine models that expand access to digital collections by combining digitally-enabled human participation with computational methods, otherwise known as human-in-the-loop approaches.”
As the Library’s digital collection expands, it needs help properly tagging and verifying the metadata attached to the content. Machine learning tools have been plugging along at this task through the pilot programs, but Library officials want humans to help verify the work is being done correctly, as well as ethically.
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Direct to Full Text of Solicitation: “Humans in the Loop: Accelerating Access and Discovery For Digital Collections”
Text of Solicitation Description
The Library of Congress is the largest library in the world, with millions of books, recordings, photographs, newspapers, maps and manuscripts in its collections. These materials are made available through various library interfaces for searching and browsing so that patrons may view (or listen to) items from the collection. Over the past few years, the Digital Innovation Labs Section (Labs) of the Digital Strategy Division has undertaken a range of programs aimed at maximizing the use of digital collections and supporting emerging research methods. This work encompasses machine learning and crowdsourcing prototypes, proof-of-concept experiments, and reports with accompanying recommendations to explore the opportunities and challenges of operationalizing emerging technologies at scale. Through various experiments, reports and events, Labs has been committed to exploring methods and approaches that responsibly integrate people and machines. User feedback, transparent and open knowledge sharing, iteration, and combining human expertise with automated methods is a central part of Labs experimental process. Now, the Library of Congress seeks to build on these initial experiments to further examine models that expand access to digital collections by combining digitally-enabled human participation with computational methods, otherwise known as human-in-the-loop approaches.
The Library is seeking a contractor to provide at least two experimental prototypes or proofs of concept for at least two human in-the-loop workflows using Library of Congress collections that are presented and tested with users. The goals in creating these prototypes are to model, test, and evaluate different ethical approaches to applying crowdsourcing and machine learning methods to Library digital collections that enhance collection usability, utility, discoverability, and user engagement