Ontology-driven knowledge base for digital humanities: Restructuring knowledge organization at the library of the Folkwang University of the Arts

Academic libraries are increasingly challenged by the need to efficiently manage and analyse vast collections of data and knowledge. The divers formats and organisation methods of these collections, ranging from traditional print media to digital archives and multimedia assets, can hinder researchers’ ability to easily access and retrieve relevant information. This paper introduces an ontology-driven knowledge base to address this issue by enabling the efficient access to knowledge in the application domain and enhancing the semantic search capabilities in the field of Digital Humanities. Our approach focuses on the development of an ontology-drive knowledge base for semantic search in academic libraries by the example of the library of the Folkwang University of Arts that captures the knowledge concepts present in the library’s archival collections. The resulting ontology framework provides a structured representation of domain knowledge, facilitating the integration of diverse data sources, including structured, semi-structured, and unstructured data from the application domain into a triple store knowledge base. By leveraging SPARQL queries generated from Large Language Model (LLM) prompts, we aim to facilitate more intuitive and effective knowledge retrieval. This approach allows users to express their information needs in a more natural and flexible way, leading to more accurate and relevant search results. We evaluate the proposed ontology-driven knowledge base in terms of its integrity, consistency, flexibility, relevance, and scalability. Our evaluation methodology includes a combination of verification and validation techniques, including automated reasoners and query results based on competence questions. Our findings demonstrate the potential of ontology engineering to enhance complex information retrieval in academic libraries. However, we also identify limitations related to processing speed for complex queries and the quality of search results. This research contributes to the field of computational archival science by providing a novel approach to semantic search in academic libraries. By enabling more precise and efficient access to knowledge, our ontology-driven knowledge base has the potential to enrich the academic and Digital Humanities landscape, empowering researchers to delve deeper into the vast resources available within these institutions.