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The Music Ontology

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Yves Raimond, Samer Abdallah, Mark Sandler, Frederick Giasson

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Centre for Digital Music, Queen Mary, University of London

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Overview

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  • Introduction
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  • Towards a web of data
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  • The Music Ontology
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  • A music-related web of data
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  • Conclusion and Future Work
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Introduction

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Music-related datasets on the web

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Linked data

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  • Resources on the Web can be far more than web pages!
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    Linked data

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    • Resources have associated representations, accessed through a dereferencing process, which can be:
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      • Human-friendly (HTML, Flash, plain text, audio, video, etc.)
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      • Machine-friendly (RDF, Microformats, RSS, etc.)
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    • Representations may hold links, allowing an agent (a program or a person) to discover more things
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    Linked data

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    Linked data

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    Vocabularies / Ontologies

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    Such data is also linked to a particular model of its domain: an ontology

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    • <http://dbtune.org/jamendo/artist/5> rdf:type foaf:Person specifies that this resource Chris@0: is a person, as defined in the FOAF ontology
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    • A performance involves some performer, a place, a time
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    • Ontologies are linked together: mo:Performance rdfs:subClassOf event:Event...
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    • ... And therefore part of the data web
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    The Data Web

    Chris@0: Turning the Web into a huge democratic, decentralized, database that can be directly consumed by applications
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    The Music Ontology

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    A framework for dealing with music-related information on the Semantic Web

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    • Complex editorial information (worflow-based)
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    • Temporal annotations
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    • Cultural information (folksonomies, social networks, etc.)
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    • Modular, adaptable, and designed to fit the needs of the community
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    • Mesh nicely with Creative Commons RDF license information
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    The Timeline Ontology

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    Expressing temporal information, eg.

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    • This performance happened the 9th of March, 1984
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    • This beat is occurring around sample 32480
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    • The second verse is just before the second chorus
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    This ontology defines:

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    • Interval (origin: OWL-Time)
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    • Instant (origin: OWL-Time)
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    • TimeLine — A backbone for addressing temporal information
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    • TimeLineMap — Relationship between two timelines
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    The Timeline Ontology

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    The Event Ontology

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    Event — An arbitrary classification of a space/time region
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    • This performance involved Glenn Gould playing the piano
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    • This signal was recorded using a XXX microphone located at that particular place
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    • This beat is occurring around sample 32480
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    The Event Ontology

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    FRBR and FOAF

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    Functional Requirements for Bibliographic Records:

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    • Work — eg. Franz Schubert's Trout Quintet
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    • Manifestation — eg. the "Nevermind" album
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    • Item — eg. my "Nevermind" copy
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    Friend of a Friend:

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    • Person
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    • Group
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    • Organization
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    • Social networking information (ask Oscar :-) )
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    Music Production concepts

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    • On top of FRBR:
    • Chris@0: Chris@0: MusicalWork, MusicalManifestation (Record, Track, Playlist, etc.), MusicalItem (Stream, AudioFile, Vynil, etc.) Chris@0: Chris@0:
    • On top of FOAF:
    • Chris@0: Chris@0: MusicArtist, MusicGroup, Arranger, Engineer, Performer, Composer, etc. — all these are defined classes: Chris@0: every person involved in a performance is a a performer... Chris@0: Chris@0:
    • On top of the Event Ontology:
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    • Others :
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    The Music production workflow

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    Current and planned extensions

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    Available extensions:

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    Possible extensions:

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    • Recording devices under Recording
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    • Mixing events dealing with Signal objects
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    • Symbolic notation under Score and AbstractTimeLine
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    • Taxonomy of music processing predicates
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    Linking Open Data

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    • A W3C Semantic Web Education and Outreach community project.
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    • Lots of open data available: Wikipedia, Geonames, Eurostat, Musicbrainz, Magnatune, etc.
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    • Let's interlink them using Semantic Web technologies — data mashups
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    • A subset of this project is the dbtune project, aiming at interlinking lots of music-related datasets using Musicbrainz as a data hub
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    Current Map

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    Conclusion and Future work

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    Conclusion

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    • RDF and HTTP provides a way to create a Web of data
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    • Vocabulary (Music Ontology) and data hub (Linking Open Data) for further interlinking of music-related datasets
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    • The MOPY Python library (Chris Sutton) allows you to manipulate Music Ontology documents without having to write one line of RDF!
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    • The GNAT software allows you to find dereferencable identifiers Chris@0: for items in your audio collection
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    Conclusion and Future work

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    Further Work

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    • Well, more interlinking!
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    • Semantic-Web-enabled music collection handler:
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      Chris@0: Is there someone nearby really liking this band and the same beer as me, so that we can have a drink tomorrow?
      Chris@0: Place my collection on a timeline and make me listen something composed in the UK in 1560, followed by a rock song recorded in the 60s
      Chris@0: Are there any other performances of this work? Give me one with a small part at 120 bpm
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    • Publishing features using Semantic Web technologies! (+interpretation rules)
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    Epilogue

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    And well, what would be a Semantic Web talk without a google map?

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    Questions ?

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