SPARQL-DJ: The MIDI Linked Data Mashup Mixer for Your Next Semantic Party

Albert Meroño-Peñuela, Rick Meerwaldt, Stefan Schlobach

Research output: Chapter in Book / Report / Conference proceedingConference contributionAcademicpeer-review


Many datasets describing musical resources are published to-
day as Linked Data, mainly focusing on metadata, notation, and audio
features. However, the availability of musical data as Linked Data is of-
ten not enough for musicians, who need additional layers of software and
queries to accomplish their workflows. Mashups are compositions created
by blending two or more pre-recorded songs, and it has been shown that
they can be generated by using SPARQL on top of MIDI music repre-
sented as Linked Data. In this demonstration, we showcase SPARQL-DJ,
a web-based application implementing those layers for the workflow of
generating MIDI mashups using Linked Data and SPARQL. The demon-
stration focuses on three parts: (1) coverage of the mashup composition
workflow; (2) scoping of input retrieval for beatmaching by broadening
text search and leveraging track annotations; and (3) management of
off-beat and dissonance.
Original languageEnglish
Title of host publicationISWC-P&D-Industry 2017 ISWC 2017 Posters & Demonstrations and Industry Tracks
Subtitle of host publicationProceedings of the ISWC 2017 Posters & Demonstrations and Industry Tracks co-located with 16th International Semantic Web Conference (ISWC 2017) Vienna, Austria, October 23rd to 25th, 2017
EditorsNadeschda Nikitina, Dezhao Song, Achille Fokoue, Peter Haase
Number of pages4
Publication statusPublished - 2017

Publication series

NameCEUR Workshop Proceedings


Dive into the research topics of 'SPARQL-DJ: The MIDI Linked Data Mashup Mixer for Your Next Semantic Party'. Together they form a unique fingerprint.

Cite this