Transforming Catalog Data into Cultural Insights: Visualizing Global Cross-media Manga Phenomena with an IFLALRM-based Metadata Schema

Abstract

Libraries are increasingly collecting subcultural content such as Japanese manga, which spreads globally through translations and cross-media adaptations (anime, films, games, etc.). However, existing catalog records cannot adequately represent or visualize the complex relationships among IFLA LRM entities. This study proposes a practical workflow to transform heterogeneous catalog data into visualization-ready metadata based on IFLA LRM. The process includes identifying derivative works, harvesting data from library catalogs, and metadata transformation. Notably, the workflow employs AI to identify metadata for editions and related merchandise often missing from library collections, followed by manual validation to ensure accuracy.

A case study of “SLAM DUNK” demonstrates how this framework operationalizes IFLA LRM structures to visualize the global dissemination of publications and cross-media networks. This approach offers significant value for libraries, including catalog data reuse, and enhanced global discovery. The workflow is adaptable to other resources, including novels, Korean webtoons, and American comics, providing a standardized framework for libraries to manage and visualize transnational cultural dissemination.