Dedicated to abstracts of recent papers that pertain to LinkedMusic's ideals
Han, Sooyeon, and JongGyu Han. 2022. “Case Study on an Integrated Interoperable Metadata Model for Geoscience Information Resources.” Geoscience Data Journal, 16. https://doi.org/10.1002/gdj3.150.
• The article covers the creation of a metadata schema to promote interoperability and characterize historically collected geoscience data. While not in the same field, the article shows the steps taken to develop a switching-across methodology, as well as an example of the methodology.
Lisena, Pasquale, Albert Meroño-Peñuela, and Raphaël Troncy. 2022. “MIDI2vec: Learning MIDI Embeddings for Reliable Prediction of Symbolic Music Metadata.” Edited by Mehwish Alam, Davide Buscaldi, Michael Cochez, Francesco Osborne, Diego Reforgiato Recupero, Harald Sack, Mehwish Alam, et al. Semantic Web 13 (3):357–77. https://doi.org/10.3233/SW-210446.
• An important problem in large symbolic music collections is the low availability of high-quality metadata, which is essential for various information retrieval tasks. In this work, the writers propose MIDI2vec, a new approach for representing MIDI ﬁles as vectors based on graph embedding techniques. Their strategy consists of representing the MIDI data as a graph, including the information about tempo, time signature, programs, and notes. Next, they run and optimize node2vec for generating embeddings using random walks in the graph. They demonstrate that the resulting vectors can successfully be employed for predicting the musical genre and other metadata such as the composer, the instrument, or the movement. Their proposal has real-world applications in automated metadata tagging for symbolic music, for example in digital libraries for musicology, datasets for machine learning, and knowledge graph completion.
McKenna, Lucy, Christophe Debruyne, and Declan O’Sullivan. 2022. “Using Linked Data to Create Provenance-Rich Metadata Interlinks: The Design and Evaluation of the NAISC-L Interlinking Framework for Libraries, Archives and Museums.” AI & SOCIETY, January, 27. https://doi.org/10.1007/s00146-021-01373-z.
• Linked data (LD) have the capability to open up and share materials, held in libraries, archives, and museums (LAMs), in ways that are restricted by many existing metadata standards. Specifically, LD interlinking can be used to enrich data and to improve data discoverability on the Web through interlinking related resources across datasets and institutions. However, there is currently a notable lack of interlinking across leading LD projects in LAMs, impacting the discoverability of their materials. In this article, LAM Linked Data projects and services were reviewed, including the Library of Congress, The German National Library, and the French National Library. Six Linked Data interlinking tools were also reviewed (AgreementMaker, LogMap, LinkItUp, The SILK Link Discovery Framework, The LIMES Link Discovery Framework for Metric Spaces, and the OpenRefine RDF Extension). The research also describes the Novel Authoritative Interlinking for Semantic Web Cataloguing in Libraries (NAISC-L) interlinking framework. Unlike existing interlinking frameworks, NAISC-L was designed specifically with the requirements of the LAM domain in mind. NAISC-L supports the linking of related resources across datasets and institutions, thereby enabling richer and more varied search queries, and can thus be used to improve the discoverability of materials held in LAMs.
Proutskova, Polina, Daniel Wolff, György Fazekas, Klaus Frieler, Frank Höger, Olga Velichkina, Gabriel Solis, et al. 2022. “The Jazz Ontology: A Semantic Model and Large-Scale RDF Repositories for Jazz.” Journal of Web Semantics 74 (October):100735. https://doi.org/10.1016/j.websem.2022.100735.
• The Jazz Ontology is a semantic model that addresses the challenges the domain of jazz poses due to musical content and performance specificities. The model builds strongly on the Music Ontology and utilizes datasets such as MusicBrainz, the Weimar Jazz Database, and LinkedJazz to build out the Ontology further. Some elements were modified, such as creating a shortcut between the Music Ontology Performance and Signal classes, and bypassing the abstract Sound concept and Recording event. For bands, the model utilizes a relationship to connect the band to its leader and relates Performers to a single Performance to allow for musicians to change on tracks. The ontology has been assessed by examining how well it supports describing and merging existing datasets and whether it facilitates novel discoveries in a music browsing application. The utility of the ontology is also demonstrated in a novel framework for managing jazz-related music information. This involves the population of the Jazz Ontology with the metadata from large-scale audio and bibliographic corpora (the Jazz Encyclopedia and the Jazz Discography). The resulting RDF datasets were merged and linked to existing Linked Open Data resources. These datasets are publicly available and are driving an online application used by jazz researchers and music lovers for the systematic study of jazz.
Putnam, Nathan. 2022. “VIAF and the Linked Data Ecosystem.” Jlist.It 13 (1). EUM-Edizioni Università di Macerata:196–202. https://doi.org/10.4403/jlis.it-12749.
• This article reviews the founding, current state, and potential future of VIAF®, the Virtual International Authority File. VIAF consists of an aggregation of bibliographic and authority data from over 50 national agencies and infrastructures, systems that follow different cataloging practices, and contain hundreds of languages. After a short history of the project, the results of surveys for implementers of linked data projects on the use of VIAF data provide suggestions for future use and sustainability.