Get everybody on board and get going: the automation of subject indexing at ZBW

Abstract

Subject indexing, i.e., the enrichment of metadata records with descriptors, is one of the core activities of libraries. Due to the proliferation of digital documents it is no longer possible to annotate every single document intellectually, which is why we need to explore the potentials of automation. At ZBW the efforts to automate the subject indexing process have started as early as 2000, and since 2014 the necessary applied research is done in-house. However, the prototypical machine learning solutions that the researchers developed were yet to be integrated into productive operations at the library. Therefore in 2020 a pilot phase was initiated (planned to last until 2024) with the task to transfer our solutions into practice by building a suitable software architecture that allows for real-time subject indexing with our trained models and the integration thereof into the other metadata workflows at ZBW. In this paper, in addition to the milestones we have reached and the challenges we faced (both on the operative and on the strategic level), we describe what the communication and cooperation with our subject librarians looked like while building this software architecture, and how we expect this interaction to evolve in the future.