Ontologies, Knowledge Graphs, and User Interfaces for Exploration of Irish Traditional Music

Musical patterns are important for many musicological tasks, such as genre classification, identifying common origins of pieces, and measuring similarities between compositions. Our previous research has defined several types of patterns in Irish traditional music and developed tools for extracting them from databases of musical scores. We now wish to enable flexible and efficient querying, open access, preservation, integration with multiple data sources, and user-friendly exploration of the data. To address these needs we use semantic web technologies. We present a music pattern ontology based on the Music Annotation Pattern (an ontology design pattern~\cite{de2022music} which formalizes key concepts in musical annotations). We develop a pipeline (Patterns2KG) to process our pattern data through the ontology. We process approximately 40 thousand compositions from two datasets to give a knowledge graph (KG) of approximately 45 million triples. We evaluate the work against pre-developed competency questions. We then elicit requirements for a graphical user interface (GUI) in collaboration with musicologists, and develop custom modular GUI software which interfaces with the KG via SPARQL queries.