The Center for Research Libraries (CRL) has reported early success from an internal pilot that uses artificial intelligence to significantly accelerate metadata generation for serial publications. The AI workflow, developed collaboratively by CRL’s Discovery and Technology team and Access Initiatives team, was designed to enhance discovery and circulation by generating item-level metadata from scanned serial issues—specifically targeting enumeration, chronology, and barcodes.
At the center of the pilot is a script created by Library Specialist Nate Florin, which extracts metadata directly from digital images. In tests, the system processed 100 serial issues in just 8.5 minutes—up to 60 times faster than previous manual methods. These gains are expected to reduce processing costs and staff workload while expanding and speeding up member access to materials. The automation allows more content to enter discovery pipelines and holdings analysis, benefiting services such as interlibrary loan fulfillment, space planning, and retention decisions.
CRL emphasized that these advancements are available to members at no additional cost. The initiative is positioned as part of CRL’s mission to increase the value of shared investment and improve operational stewardship of the collection. Amy Wood, head of the Discovery and Technology team, noted the transition from “baby steps” to a faster, more scalable system for access.
The organization continues to fine-tune the process to improve consistency and handle edge cases. Planned extensions of the model include its application to textbook metadata and the generation of Local Holdings Records. These developments aim to further expand the range and speed at which CRL’s materials can be accessed and used in teaching and research.
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