Kumulative Dissertation, Otto-Friedrich-Universität Bamberg, 2024

Various sources suggest that Knowledge Graphs (KGs) despite being built upon decades-old foundations, are currently in the midst of a hype. The reason for this is rooted in the variety of applications, for which KGs can be used. While KGs have been employed successfully in many application domains such as information retrieval and recommender systems, recent research in machine learning and artificial intelligence highlights the opportunities that KGs provide in these domains. However, like any other hyped technology, KGs have been subject to inflated expectations, which has led a certain disillusionment in the recent years. To contribute to the further maturation of KGs towards a state with a deep and realistic understanding of the technology, this cumulative doctoral thesis investigates three novel applications of RDF-based KGs.

The first application leverages the large open-domain KG Wikidata to identify semantically useful paths between entities. These paths are then used as the basis for generating entity relationship explanations, which are to be displayed in the knowledge panels on the result pages of web search engines with the goal of satisfying the users' information need more quickly. The second application establishes a bidirectional knowledge exchange between (LaTeX-based) research publications and Scientific Knowledge Graphs (SKGs), one category of domain-specific KGs, through custom import and export commands. This technology is intended to narrow the gap between research publications and SKGs to facilitate the shift towards the envisaged KG augmented research. The third application leverages the reasoning capabilities of the RDF ecosystem to validate software repositories, represented as KG fragments, against quality criteria that they should meet according to the type of the respective project. In light of the still ongoing reproducibility crisis, the validation of software repositories against the FAIR principles is examined in particular.

Based on the insights obtained from the investigation of the three applications, opportunities, challenges, and recommendations for the utilization of KGs are derived. Some of the addressed aspects elaborate on topics discussed in previous work while others add novel points to this line of research. To give some examples, the aspects include remarks on the ability of KGs to integrate and interconnect heterogeneous data, the complexity of the RDF ecosystem, and data access facilities and interfaces.