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An #ESWC 2022 tutorial |
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Music encoding, the representation of symbolic music information in a machine-accessible form, is critical to a variety of fields and areas of study, including computational or digital musicology, digital editions, symbolic music information retrieval, and digital libraries. The Linked Data Interest Group of the Music Encoding Initiative (MEI) brings together music encoding specialists with experts in Web science and knowledge organization and regularly organizes training events focusing on applications of Linked Data to music encodings.
We propose a full-day tutorial for ESWC 2022 describing the application of semantic technologies to the domain of music encoding. The tutorial is aimed at members of the Semantic Web and Linked Data community with an interest in music, and does not require participants to have previous knowledge of music encoding. During the session, we will provide a high-level overview of music encoding technologies, briefly covering their history and purpose, some terminology, and relevant applications of Linked Data and Semantic Web approaches in this context. Real-life examples and hands-on experience with exercises in interlinking, querying, and annotating various music-related datasets (e.g., RISM, DOREMUS, JazzCats) will guide participants through the sessions.
This tutorial aims to raise awareness of music-specific approaches within the Semantic Web and Web science communities. It is thus intended to help build bridges between communities and promote discussion and exchange about music-related Semantic Web topics. By providing an overview of the state of the art in music encoding, existing music-related ontologies, SPARQL endpoints, and datasets, it seeks to offer points of departure for further engagement with the subject matter.
The main focus of the tutorial will be on interlinking music encodings and music datasets through the use of Linked Data (RDF) and MEI 4.0. During the session, we will provide a high-level overview of music encoding technologies with basic examples to introduce the subject in an accessible way, allowing participants to follow along at their own pace. We will briefly cover the history and purpose of music encodings, some terminology, and relevant applications of Linked Data and Semantic Web approaches in this context. We will take a closer look at some real-life examples, and get hands-on experience with exercises in interlinking, querying, and annotating various datasets (e.g., RISM, DOREMUS, JazzCats).
We expect to impart a basic awareness of music encoding technologies and of the affordances of music encodings as Semantic Web resources. Although time constraints restrict the depth of detail we will be able to explore, attendees will leave with a better idea of how their research might contribute to, and benefit from, approaches to music encoding, and will be equipped with sufficient vocabulary and understanding as well as an overview of existing tools, literature, and training events to independently pursue further knowledge on this topic.