TY - GEN
T1 - The MIDI linked data cloud
AU - Meroño-Peñuela, Albert
AU - Hoekstra, Rinke
AU - Gangemi, Aldo
AU - Bloem, Peter
AU - de Valk, Reinier
AU - Stringer, Bas
AU - Janssen, Berit
AU - de Boer, Victor
AU - Allik, Alo
AU - Schlobach, Stefan
AU - Page, Kevin
N1 - Publisher Copyright:
© Springer International Publishing AG 2017.
PY - 2017
Y1 - 2017
N2 - The study of music is highly interdisciplinary, and thus requires the combination of datasets from multiple musical domains, such as catalog metadata (authors, song titles, dates), industrial records (labels, producers, sales), and music notation (scores). While today an abundance of music metadata exists on the Linked Open Data cloud, linked datasets containing interoperable symbolic descriptions of music itself, i.e. music notation with note and instrument level information, are scarce. In this paper, we describe the MIDI Linked Data Cloud dataset, which represents multiple collections of digital music in the MIDI standard format as Linked Data using the novel midi2rdf algorithm. At the time of writing, our proposed dataset comprises 10,215,557,355 triples of 308,443 interconnected MIDI files, and provides Web-compatible descriptions of their MIDI events. We provide a comprehensive description of the dataset, and reflect on its applications for research in the Semantic Web and Music Information Retrieval communities.
AB - The study of music is highly interdisciplinary, and thus requires the combination of datasets from multiple musical domains, such as catalog metadata (authors, song titles, dates), industrial records (labels, producers, sales), and music notation (scores). While today an abundance of music metadata exists on the Linked Open Data cloud, linked datasets containing interoperable symbolic descriptions of music itself, i.e. music notation with note and instrument level information, are scarce. In this paper, we describe the MIDI Linked Data Cloud dataset, which represents multiple collections of digital music in the MIDI standard format as Linked Data using the novel midi2rdf algorithm. At the time of writing, our proposed dataset comprises 10,215,557,355 triples of 308,443 interconnected MIDI files, and provides Web-compatible descriptions of their MIDI events. We provide a comprehensive description of the dataset, and reflect on its applications for research in the Semantic Web and Music Information Retrieval communities.
KW - Linked data
KW - MIDI
KW - Music interoperability
UR - http://www.scopus.com/inward/record.url?scp=85032210624&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-68204-4_16
DO - 10.1007/978-3-319-68204-4_16
M3 - Contribución a la conferencia
AN - SCOPUS:85032210624
SN - 9783319682037
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 156
EP - 164
BT - The Semantic Web – ISWC 2017 - 16th International Semantic Web Conference, Proceedings
A2 - Fernandez, Miriam
A2 - d’Amato, Claudia
A2 - Tamma, Valentina
A2 - Cudre-Mauroux, Philippe
A2 - Lecue, Freddy
A2 - Lange, Christoph
A2 - Sequeda, Juan
A2 - Heflin, Jeff
PB - Springer Verlag
T2 - 16th International Semantic Web Conference, ISWC 2017
Y2 - 21 October 2017 through 25 October 2017
ER -