The Center for Research Libraries (CRL) will participate in a program at Canisius University on September 30, 2025, where Amy Wood, Director for Collections Access and Technology, will co-present research on cooperative cataloging models with graduate researcher Edidiong Ibokete.
The session, hosted by Dr. Sana Spector, will showcase how Ibokete and Wood designed and tested a marketplace-style algorithm that offers greater flexibility and resilience than prior approaches to cooperative cataloging networks. Their work addresses a significant challenge in metadata creation by using configurable rules that respect priorities such as language or cataloging level, while maintaining fairness and balance across institutions.
“Reducing cataloging backlogs and achieving equitable distribution of expertise are long-standing challenges for research libraries,” said Wood. “We’re pleased by the success of the pilot and grateful for Edidiong’s work to bring this concept to life through a practical application of innovative technology.”
Andrea Dunzt, CRL’s Chief Operating Officer, added: “By testing marketplace-style models, CRL is helping members reduce costs, increase efficiency and ensure that specialized collections receive the attention they deserve."
This initiative reflects CRL’s role as a collaborative laboratory for research libraries, developing and piloting solutions that no single institution could achieve alone. The project was made possible with data insights from CRL members, underscoring the value of the consortium as a collective engine of innovation.
“I am grateful to CRL for the opportunity to contribute to this important initiative in collaborative library systems,” said Ibokete. “Through this experience, I strengthened my expertise in algorithm design, data-driven problem solving, and building systems that prioritize both equity and practical outcomes.”
Wood also expressed her appreciation for the project participants: “We were very pleased with what we learned and the algorithm's success. Dozens of libraries provided information to build the algorithm; that gave us confidence that we were working on something of real value, and we couldn’t have done it without their input.” CRL will share findings broadly and seek opportunities to expand testing with member institutions in 2026.