Publishing and Performing Digital Musicology on the Web: Signature Sound Vienna

Signature Sound Vienna is an interdisciplinary digital musicology investigation of the Vienna Philharmonic Orchestra’s New Year’s Concert series, conducted by reference to a collection of relevant concert recordings and scores assembled for this purpose. In this paper, we present an overview of the workflows and software tools developed co‑creatively between the project’s music scholars and technologists, aiming to facilitate the publication, analysis and dissemination of findings pertaining to musicological research data while adhering to FAIR principles of data management. These workflows and tools include automated conversion scripts to publish metadata of large collections of music media, retrieved and validated using the MusicBrainz Picard Tagger, as Linked Data adhering to the Music Ontology; mei‑friend, a browser‑based editor for music encodings; Listen Here!, an environment for tool‑assisted close listening to score‑aligned collections of performance recordings; and Primal, a platform for review and interaction with music annotation Linked Data. Building on Web standards and established ontologies, including the Solid platform for social Linked Data, the Web Annotation Data Model, the Music Annotation Ontology and the schema of the Music Encoding Initiative (MEI), our modular tools integrate on shared Linked Data structures. This supports complex musicological investigations through comparatively simple applications focusing on specific tasks and modalities, as well as enabling further extensions beyond the scope of our project. We present a case study of the use of this approach within our own scholarly investigations, showcasing findings from performance analyses of collections of the most frequently performed compositions of the New Year’s Concert series, and discuss the implications of our approach on broader digital musicology contexts.