On providing semantic alignment and unified access to music library metadata

Abstract

A variety of digital data sources-including institutional and formal digital libraries, crowd-sourced community resources, and data feeds provided by media organisations such as the BBC-expose information of musicological interest, describing works, composers, performers, and wider historical and cultural contexts. Aggregated access across such datasets is desirable as these sources provide complementary information on shared real-world entities. Where datasets do not share identifiers, an alignment process is required, but this process is fraught with ambiguity and difficult to automate, whereas manual alignment may be time-consuming and error-prone. We address this problem through the application of a Linked Data model and framework to assist domain experts in this process. Candidate alignment suggestions are generated automatically based on textual and on contextual similarity. The latter is determined according to user-configurable weighted graph traversals. Match decisions confirming or disputing the candidate suggestions are obtained in conjunction with user insight and expertise. These decisions are integrated into the knowledge base, enabling further iterative alignment, and simplifying the creation of unified viewing interfaces. Provenance of the musicologist's judgement is captured and published, supporting scholarly discourse and counter-proposals. We present our implementation and evaluation of this framework, conducting a user study with eight musicologists. We further demonstrate the value of our approach through a case study providing aligned access to catalogue metadata and digitised score images from the British Library and other sources, and broadcast data from the BBC Radio 3 Early Music Show.

Using Note-Level Music Encodings to Facilitate Interdisciplinary Research on Human Engagement with Music

“…into linked data representations of different types of musical information. Historically, however, much of the work on linked data has developed methods for linking different musical documents (Weigl et al, 2019b). An exception is Fields et al 2011, who explored integrating human annotations of musical form into a linkeddata framework, and more recent work has begun to incorporate note-level encodings into these frameworks, facilitating content-based search and indexing.…”

Interweaving and Enriching Digital Music Collections for Scholarship, Performance, and Enjoyment

“…Methods for capturing the semantics of scholarly workflows were studied, analysing and comparing steps needed to achieve useful results in music(ologic)al tasks [20]. Other work, in the SLICK-MEM and SLoBR projects immediately preceding Transforming Musicology [6,26], focussed on the problems of aligning multiple datasets compiled with inconsistent formats or standards. Another study around querying interlinked classical music catalogues [9] exposed limitations of SPARQL, the query language in general use for searching Linked Data.…”

An MEI-based standard encoding for hierarchical music analyses

“…Here we identify the requirements of a standard for the representation of hierarchical music analyses, taking into account the observations of the previous sections. The encoding must allow linked data requirements as detailed in [34]. Analytical and musical information need to be associated, and to facilitate this it should be possible to record the analysis and music in the same file.…”

“…To be properly usable in the digital domain, a representation of an analysis needs also to be readable by software. It needs to be searchable and, with the growth of the semantic web, it needs also to be linkable [34]. After reading an analysis, it can be useful also for an application to be able to "play" or render it either visually or acoustically.…”