Abstract:

In the age of digital intelligence, traditional cataloging systems are facing challenges and are unable to meet the requirements for knowledge production based on intelligent data generation. The Shanghai Library has improved the traditional cataloging process, incorporated the concept of expert collaborative knowledge production and full-process management based on the concept of crowdsourcing, and designed an expert collaborative knowledge production system for full-process management— the Genealogy Joint Cataloging System. This system could realize the standard control across network domains in the cataloging process by using the existing basic knowledge base of people, institutions, places, times, events, etc. of the Library. Genealogy cataloging experts from different institutions can share basic knowledge. The existing knowledge in the library can jointly supplement and enrich the knowledge missing in the cataloging process, build knowledge associations and semantic links in real time, and connect the cataloging process and knowledge production with the genealogy knowledge service platform, so that knowledge production and knowledge services are seamlessly linked. Together, we have achieved full-process management of procurement, donation, description, duplication checking, quality inspection, normative control, knowledge services, and related data release. On this basis, the path of AI genealogy cataloging data review based on the big language model was explored.

Key words: Digital humanities, Full-process data processing, Joint cataloging, Crowdsourcing, AIGC