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Title
Abstract
Project Summary
Executive Summary
Introduction
Related Work
Music Ontologies, Datasets, and Knowledge Graphs
Music Metadata Similarity Linking
Chordal Data in Choco
From Chordal Data to Jams Datasets
Jamification of Datasets
Linked Data Cloud
References
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Computer Science
Database Systems

D2.4: Methods for interlinking knowledge graphs (V1.0)

Profile image of Simon HollandSimon Holland

2022, Zenodo (CERN European Organization for Nuclear Research)

Abstract

One of the key missions of the Polifonia project is to build and interlink knowledge graphs of European musical cultural heritage. These interconnected music knowledge graphs act as a data backbone for the project. This deliverable is centred around one of the ten Polifonia pilots: INTERLINK. The INTERLINK pilot is not bound to a specific institutional dataset, collection or use case; but rather summarises the common needs of all pilots of representing their data as music knowledge graphs, and finding meaningful connections among them. Existing work in the relevant areas of knowledge engineering, knowledge graph construction, and knowledge graph interlinking is promising but presents a number of pitfalls in its direct application to Polifonia from the point of view of achieving this knowledge graph building and interlinking: (a) existing knowledge engineering methodologies do not account for "in-between" knowledge graph construction processes that are not fully distributed nor local; (b) in an integrated vision of European musical cultural heritage through knowledge graphs, both musical content and its 'context' or metadata need to co-exist; and (c) no current techniques address the issue of finding missing links between different music knowledge graphs at scale, accounting for this coexistence of musical content and context in the same knowledge graph. This deliverable describes our efforts, particularly gathered in Polifonia's WP2 and Task T2.3, in addressing these challenges, delivering: (a) a scalable methodology for knowledge graph construction that is well suited for the project and sits in-between the two classic extremes of ontology engineering; (b) a music knowledge graph construction framework that leverages modules of the Polifonia Ontology Network and the SPARQL Anything tool; and (c) a music knowledge graph interlinking framework, based on both heuristics and neural network-based link prediction through music knowledge graph embeddings. The latter two are evaluated in two different use-cases, the ChoCo-KG chord annotation knowledge graph, and the MIDI2vec music knowledge graph interlinking method, with encouraging results.

Related papers

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Automatic interlinking of music datasets on the semantic web
Mark Sandler

2008

In this paper, we describe current efforts towards interlinking music-related datasets on the Web. We first explain some initial interlinking experiences, and the poor results obtained by taking a naïve approach. We then detail a particular interlinking algorithm, taking into account both the similarities of web resources and of their neighbours. We detail the application of this algorithm in two contexts: to link a Creative Commons music dataset to an editorial one, and to link a personal music collection to corresponding web identifiers. The latter provides a user with personally meaningful entry points for exploring the web of data, and we conclude by describing some concrete tools built to generate and use such links.

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Interlinking Music-Related Data on the Web
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IEEE Multimedia, 2000

I nformation management is an important part of multimedia, covering the administration of public and personal collections, the construction of large editorial databases, and the storage of analysis results. Applications for each of these aspects of multimedia management have emerged, with notable examples being Greenstone (see http://www.greenstone.org) for digital libraries, iTunes for personal media-collection management, MusicBrainz (see http://musicbrainz.org) for classification data, and traditional relational databases for managing analysis results.

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Assessing Music Ontologies for the development of a complex database
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The increasing volume and diversity of musical information have been creating a challenge for the uniform creation, reuse, and sharing of this kind of information. As part of addressing this challenge, there has been a growing interest in musical ontologies, as a technique to support the sharing of heterogeneous musical information, both for commercial and cultural dissemination purposes. Motivated by a specific objective, in the context of the development of an information system on musicians and respective artistic production and professional career, existing ontologies for the music domain, in general, were surveyed. The purpose of this study is to support the hypothesis that this approach can not only support the specific requirement of that objective but also facilitate interoperability with other existing systems, with databases and catalogs built with multiple technical solutions.

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Reinier de Valk

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SEMU: A Semantic Knowledge Management System of Musical Information
somjit Arch-int

Entertainment Computing, 2015

The diverse data types of musical information domain including binary and text-based structures create semantic gaps between the entities of different data formats. This leads to difficulties in analyzing, capturing and managing entities of the domain. In this paper, we present a semantic knowledge management system, called SEMU, to efficiently managing musical information. We propose SEMU ontology to capture information extracted from various data types and sources. In order to extract information from raw data, we use Musical Information Retrieval techniques for audio files and Natural Language Processing techniques for text-based formats. We develop a rule-based solution to enrich the system knowledge base. Later, we provide a web application with seamless integration between SEMU knowledge base and user interface to enable users to benefit from the advantages of the SEMU system.

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Characterizing the Landscape of Musical Data on the Web: state of the art and challenges
Simon Holland

2017

Musical data can be analysed, combined, transformed and exploited for diverse purposes. However, despite the proliferation of digital libraries and repositories for music, infrastructures and tools, such uses of musical data remain scarce. As an initial step to help fill this gap, we present a survey of the landscape of musical data on the Web, available as a Linked Open Dataset: the musoW dataset of catalogued musical resources. We present the dataset and the methodology and criteria for its creation and assessment. We map the identified dimensions and parameters to existing Linked Data vocabularies, present insights gained from SPARQL queries, and identify significant relations between resource features. We present a thematic analysis of the original research questions associated with surveyed resources and identify the extent to which the collected resources are Linked Data-ready.

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Tools for Music Bibliographic Network Analysis
Yun F . Henshaw

DLfM '17 Proceedings of the 4th International Workshop on Digital Libraries for Musicology, 2017

Many metadata repositories have been used to enrich music information retrieval applications, focusing on topics such as recorded music or performance catalogues. We present a database of biblio-graphic information that focuses on indexing writings on music, containing expert-curated subject terms from a controlled vocabulary , embedded inter-lingual equivalencies of these terms, and links that connect works and terms with canonical reference identifiers. An ontology of these terms, as well as an API to programatically access them, is under development for use in exploring and analyzing musicological bibliographic networks across domains, languages, and cultures.

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