D2.1: Ontology-based knowledge graphs for music objects (V1.0)
Creators: name: Meroño Peñuela, Albert
name: De Berardinis, Jacopo
name: Martinez Pandiani, Delfina Sol
name: Carriero, Valentina
name: Wigham, Mari
name: Poltronieri, Andrea
name: Ciroku, Fiorela
name: Guillotel-Nothmann, Christophe
name: Rigaux, Philippe
Publisher: name: Zenodo
Year: 2021

description: This deliverable describes the results of the WP2 Musical Heritage Knowledge Graphs in its first 12 months with respect to the task T2.1: Ontology-based knowledge graphs for music objects. The project, and specifically WP2 and T2.1, uses knowledge engineering as a process and methodology to build ontologies and knowledge graphs that facilitate large-scale integration of various sources of musical heritage data. In this deliverable, we focus on music objects broadly understood as artefacts carrying musical content and meaning (recordings, music notation, musical theory, musical features) rather than contextual descriptions (e.g. composer, year of performance). New conceptualisations, in the form of ontologies, are needed to formalise the semantics of this domain and allow the creation of interoperable knowledge graphs from datasets. To achieve this, we apply a well-known ontology design methodology, eXtreme Design (XD), which emphasises: (i) ontology reuse and modularity through the design and use of Ontology Design Patterns (ODPs); and (ii) gathering a comprehensive inventory of ontological requirements through competency questions (CQs). To implement (i), we survey existing ontologies and ODP that are relevant to the domain, and existing datasets from Polifonia’s WP1 Pilots – building on the dataset survey work from WP1 [1]– and from the Music Information Retrieval (MIR) community; to implement (ii) we follow a thorough process of collecting and normalising CQs from the stories and personas that stem from the Pilots of WP1. This ensures an agnostic approach in which Polifonia designs a specific conceptualisation of music (elements, reception, actors, events, etc.) that reflects original and innovative theory building aspirations, while providing a good compromise with respect to reusing existing models and theories. As a result of this, we report on the first version of the Polifonia Ontology Network (PON), a network of ontologies that model the domains emanating from such stories and personas in the Core, Musical Performance, Musical Composition, Musical Feature, Source, Instrument, Comparative Measure, Music Emotion, Bell, and Metadata ontology modules. Even though the evaluation of this knowledge engineering work is the specific objective of another task (T2.5 and D2.7, D2.8: Ontology testing and evaluation report), we report here on preliminary efforts to evaluate the adequacy and correctness of the PON at effectively answering the project’s CQs, through testing automation and expert validation; and its applicability in a real-world, demanding setting in which we used the developed ontologies to annotate, model and exchange data in a demonstration at a top, internationally renowned event: the AI &amp; Music Festival at the Sónar Barcelona International Music Festival (27-28 October 2021, Barcelona). Finally, we also pave the way into the project-wide, large-scale usage of the PON to annotate all the identified datasets in Polifonia (through [1] and here), MIR and beyond, effectively creating the Polifonia Knowledge Graph (PKG). The specific details on how this is achieved will follow in a further deliverable (D2.4: Methods for interlinking knowledge graphs), but we offer here a roadmap and the first methods we have created to interlink musical heritage knowledge graphs.