Automated Subject Cataloguing at the German National Library

Abstract

The German National Library (DNB), as mandated by the German National Library Act of 2006, is responsible for collecting all German cultural artefacts, including digital and non-physical resources. To meet this requirement, DNB engaged in a Machine Learning (ML) project to improve metadata generation. After a while the project transitioned to a completely automated approach called subject cataloguing machine using Annif, an AI tool from the National Library of Finland, incorporating ML or subject indexing and metadata creation. This AI development relies heavily on the expertise of librarians, as AI tools are at times not fully accurate. While AI enhances efficiency, librarians and cataloguing specialists remain essential to ensure quality. The transition faced challenges, including limited resources, ethical issues, a diversified workforce’s attitude towards AI, and the complexities of copyright laws. Despite these challenges, the integration of EMa has improved the generation and accessibility of metadata within DNB services. While AI can enrich librarians’ skills, it cannot replace them. Mistakes encountered along the way should be viewed as learning opportunities, and future advancements should involve collaborative, diverse teams to continue refining the integration of AI in metadata management.