Cultural heritage data, particularly from colonial contexts, frequently presents an incomplete and biased view, reflecting historical institutional priorities more than contemporary knowledge requirements. Consequently, knowledge graphs derived from these records often contain incomplete, fragmented, and skewed data, including absent attributes or values, missing semantic links, and under-represented perspectives. This work addresses the challenge of knowledge discovery under such limitations, presenting a real-world case study on the provenance research of colonial cultural heritage. We present a task-aware design method for building a tool to facilitate this process. The design approach of this application is rooted in a Knowledge Discovery in Database (KDD) framework and is particularly novel due to its formalisation and operationalisation of three distinct types of semantic association: explicit, abstract, and implicit. These semantic associations, grounded in domain interpretation, are crucial for bridging data gaps where user information needs cannot be directly met by existing data. We further demonstrate how these associations can be effectively communicated through user interface components, enabling users to infer new knowledge. We evaluated the resultant application through a user study among domain experts to assess its efficacy. The evaluation confirms the effectiveness of the tool in enabling new knowledge discovery and reveals opportunities to improve the representation of the underlying data, as users could successfully infer insights even when information was missing or poorly captured in the original data sets.

Abstract The BookSampo Linked Data portal was deployed in 2011 by the Finnish Public Libraries and has today nearly 2 million annual users. Its Linked Data covers virtually all Finnish fiction literature but the data has not been used for data analyses in Digital Humanities. This paper discusses how the Knowledge Graph can be used for literary research in two ways: First, a new BookSampo 2.0 Portal user interface is presented, based on faceted semantic search with seamlessly integrated data‐analytic tools for Digital Humanities research as suggested in the Sampo Model. This application makes it possible to analyze the data without programming skills. Second, the BookSampo SPARQL endpoint API can be accessed directly by SPARQL querying and scripting, using tools such as Jupyter Notebooks. The analysis results presented suggest interesting spatial, temporal, and topical trends in how the Finnish fiction literature has evolved during the last decades. The approach and tools presented in this paper can be used for analyzing literary landscapes developments in other countries as well.