際際滷

際際滷Share a Scribd company logo
Towards a musical Semantic Web Yves Raimond Centre for Digital Music, Queen Mary, University of London May 6th, 2007
Overview Introduction Web Web of data The Semantic Web RDF Making sense of the data Content negotiation The Music Ontology The Timeline ontology The Event ontology FRBR + FOAF Music  production  specific concepts Workflow information Levels of expressiveness Extensions And now?? Linking open data on the Semantic Web Two applications
Introduction  Web  1. I ask my favourite search engine for  Lonah creative commons song   Looking for Creative Commons-licensed song from the French band  Lonah
Introduction  Web  Looking for Creative Commons-licensed song from the French band  Lonah 2. I read the  context 油of each of the first results 3. The second one seems ok... 4. I reach this  last.fm  page: 5. According to the tags, it looks like the band I am looking for... 6. I read Music available on ... and decide to visit the linked page 7. I reach the Jamendo website 8. I launch a search for  Lonah , and, finally:
Introduction  Web  Now:  Ask your computer to do the same thing! Some requirements emerging from this scenario: - I need an entry point: the  search engine - I need to understand the  context  of the links - I need to find my way into the  web maze
Introduction  Web of data Turning the Web into a huge, semantic, democratic database in order to make machines able to look by themselves for particular informations KB1 KB2 KB3 KB4 Application1 Application 2
The Semantic Web Resources on the Web can be far more than just web pages! http://moustaki.org/foaf.rdf#moustaki  is a resource representing  me http://dbtune.org/jamendo/band/lonah  is a resource representing the band  Lonah When  HTTP-GET ting, Let's leave fancy HTML pages for humans, and let's  provide some useful descriptions for the machine! Resource Description Framework http://dbtune.org/jamendo/band/both http://dbtune.org/jamendo/artist/5 Both http://xmlns.com/foaf/0.1/Group
Ontologies - Making sense of the data Ontologies , to map these  resources and properties (links) 油to  real-world objects and  relationships Providing a COMMON UNDERSTANDING An  Album 油has several  Tracks , a  name , a  release date ... A  Performance 油has one  location , one  time , some  performers , ... Ontologies are also described in  RDF Instance data  refers  to ontologies through  RDF triples such as: < http://dbtune.org/jamendo/artist/5 > rdf:type < http://purl.org/ontology/mo/Musicartist > < http://dbtune.org/jamendo/artist/5 >  foaf:name  Both
Content negotiation http://dbtune.org/jamendo/artist/5 <mo:MusicArtist rdf:about=&quot;http://dbtune.org/jamendo/artist/5&quot;> <foaf:based_near rdf:resource=&quot;http://dbpedia.org/France&quot;/> <foaf:homepage rdf:resource=&quot;http://www.both-world.com&quot;/> <foaf:img rdf:resource=&quot;http://img.jamendo.com/artists/b/both.jpg&quot;/> <foaf:name rdf:datatype=&quot;&xsd;string&quot;>Both</foaf:name> </mo:MusicArtist> HTML for human consumption RDF for machine consumption And now, let's make both the  human  油and the  machine  happy!
The Music Ontology Problem:  no agreed ways of dealing with music-related information on the Semantic Web Solution:  Let's launch a community project, based on previous ontology engineering efforts! http://musicontology.com/ Several facets [Pachet]: Complex  editorial  information Acoustic  information ( cultural  information)
The Timeline ontology First thing to address: representing  temporal information This performance happened the 9 th  of March, 1984  This beat is occurring around sample 32480  The second verse is just before the second chorus ... Only four concepts:  Instant ,  Interval ,  TimeLine  (and  TimeLineMap )
The Event ontology We need a way to classify space/time regions : Performances, recordings, beats, verses, composition, ...
FRBR + FOAF FRBR: Functional Requirements for Bibliographic Records We use three FRBR concepts:   Work Manifestation Item The  Expression  concept seemed to fuzzy for being used: whole  workflow  between a work and its manifestation FOAF: Friend-of-a-friend Person Group Organization ... and the relationship vocabulary (married, brother of, etc.)
Music  production  specific concepts On top of FRBR: MusicalWork ,  MusicalManifestation  ( Album ,  Track ,  Playlist,  etc.) MusicalItem  ( Stream , a particular  Vynil , etc.)   On top of FOAF: MusicArtist  and  MusicGroup  (defined classes) Arranger ,  Engineer ,  Performer ,  Composer , etc. (same thing) On top of the Event ontology: Composition ,  Arrangement ,  Performance ,  Sound ,  Recording Others: Signal ,  Score ,  Genre ,  Instrument , etc.
Workflow  information
Levels of expressiveness Flexibility of the ontolog y - Level 1:  purely editorial  This track is on that particular album and that compilation and was created by that artist - Level 2:  introducing events  This is a recording of this particular musician playing that jazz-rock arrangement of that particular piece - Level 3:  introducing event decomposition  In this performance, this key was played at this particular time by this person,  who was playing the piano
Extensions Lots of  anchor points  (instrument, genre, signal, timeline, etc.) Already several extensions available: -  Musical feature ontology : uses  Event  as a way to classify  features on a signal' timeline -  Instrument taxonomy : thanks to Musicbrainz! -  Genre taxonomy : thanks to Wikipedia/DBPedia -  The Key ontology Other possible extensions: - Audio recording devices under the  Recording  concept? -  Mixing  events dealing with  Signal  objects? - Sound cognition under the  Sound / Listener  concepts? - Symbolic music notation under  Score ? - Chord ontology?
Linking open data on the Semantic Web W3C' Semantic Web Education and Outreach community project Lots of  open data  available: Wikipedia, Geonames, Musicbrainz, creative commons  repositories, etc. Let's interlink them using Semantic Web technologies: DATA MASHUPS So far: - Jamendo - Magnatune - Musicbrainz - DBPedia - GeoNames - RDF book mashup - ...
And now?? - Your audio files are just other  items  of a particular  manifestation , which has an URI  - Store the corresponding statements in your SW-enabled application - And your collection gets access to the whole web of knowledge (well, in its current  state:-) ) Give me all musical works composed in a city with more than 500 000 inhabitants Is there someone nearby really liking this band and the same beer as me, so that we can have a drink tomorrow? 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 Give me all Jimmy Hendrix songs played by Brass Bands with at least 5 members Are there any other performances of this work? Give me one with a small part at 120 bpm
Thank you!!
Ad

Recommended

Publishing and interlinking music-related data on the Web
Publishing and interlinking music-related data on the Web
Yves Raimond
Combining Social Music and Semantic Web for music-related recommender systems
Combining Social Music and Semantic Web for music-related recommender systems
Alexandre Passant
Ontology Engineering: Ontology Use
Ontology Engineering: Ontology Use
Guus Schreiber
Semantics-aware Content-based Recommender Systems
Semantics-aware Content-based Recommender Systems
Pasquale Lops
Conception et R辿alisation dune application de Gestion SCOLAIRE
Ghizlane ALOZADE
Mining the social web for music-related data: a hands-on tutorial
Mining the social web for music-related data: a hands-on tutorial
Ben Fields
Recommending for the World
Recommending for the World
Yves Raimond
(Some) pitfalls of distributed learning
(Some) pitfalls of distributed learning
Yves Raimond
Developing A Semantic Web Application - ISWC 2008 tutorial
Developing A Semantic Web Application - ISWC 2008 tutorial
Emanuele Della Valle
Aplicaii Web Semantice - Descriere Proiect
Aplicaii Web Semantice - Descriere Proiect
Vlad Posea
Mashed Up Playlist
Mashed Up Playlist
David Peterson
Linked Data Publication of Live Music Archives
Linked Data Publication of Live Music Archives
seanb
S. Dixon, C. Mesnage, B. Norton. LinkedBrainz Live
S. Dixon, C. Mesnage, B. Norton. LinkedBrainz Live
MusicNet
Drupal case study: ABC Dig Music
Drupal case study: ABC Dig Music
David Peterson
Realizing a Semantic Web Application - ICWE 2010 Tutorial
Realizing a Semantic Web Application - ICWE 2010 Tutorial
Emanuele Della Valle
Introduction to Fast by Professor Mark Sandler
Introduction to Fast by Professor Mark Sandler
FASTIMPACT
Ontologies for music from a digital library practitioner's perspective
Ontologies for music from a digital library practitioner's perspective
Jenn Riley
Introduction to Semantic Web for GIS Practitioners
Introduction to Semantic Web for GIS Practitioners
Emanuele Della Valle
J-P. Fauconnier, J. Roumier. Musonto - A Semantic Search Engine Dedicated to ...
J-P. Fauconnier, J. Roumier. Musonto - A Semantic Search Engine Dedicated to ...
MusicNet
Usage of Linked Data: Introduction and Application Scenarios
Usage of Linked Data: Introduction and Application Scenarios
EUCLID project
Mapping, Interlinking and Exposing MusicBrainz as Linked Data
Mapping, Interlinking and Exposing MusicBrainz as Linked Data
Peter Haase
Music Objects to Social Machines
Music Objects to Social Machines
David De Roure
Future of Web 2.0 & The Semantic Web
Future of Web 2.0 & The Semantic Web
is20090
Sonia Pascua IFLA 2018
Sonia Pascua IFLA 2018
Sonia Pascua
Lee Iverson - How does the web connect content?
Lee Iverson - How does the web connect content?
Museums Computer Group
Linked data and Muruca @ COST a32 - Munich
Linked data and Muruca @ COST a32 - Munich
Christian Morbidoni
Semantic Web Landscape 2009
Semantic Web Landscape 2009
LeeFeigenbaum
Semantic Web Good News
Semantic Web Good News
Frank van Harmelen
Time, Context and Causality in Recommender Systems
Time, Context and Causality in Recommender Systems
Yves Raimond
Deep Learning for Recommender Systems
Deep Learning for Recommender Systems
Yves Raimond

More Related Content

Similar to Towards a musical Semantic Web (20)

Developing A Semantic Web Application - ISWC 2008 tutorial
Developing A Semantic Web Application - ISWC 2008 tutorial
Emanuele Della Valle
Aplicaii Web Semantice - Descriere Proiect
Aplicaii Web Semantice - Descriere Proiect
Vlad Posea
Mashed Up Playlist
Mashed Up Playlist
David Peterson
Linked Data Publication of Live Music Archives
Linked Data Publication of Live Music Archives
seanb
S. Dixon, C. Mesnage, B. Norton. LinkedBrainz Live
S. Dixon, C. Mesnage, B. Norton. LinkedBrainz Live
MusicNet
Drupal case study: ABC Dig Music
Drupal case study: ABC Dig Music
David Peterson
Realizing a Semantic Web Application - ICWE 2010 Tutorial
Realizing a Semantic Web Application - ICWE 2010 Tutorial
Emanuele Della Valle
Introduction to Fast by Professor Mark Sandler
Introduction to Fast by Professor Mark Sandler
FASTIMPACT
Ontologies for music from a digital library practitioner's perspective
Ontologies for music from a digital library practitioner's perspective
Jenn Riley
Introduction to Semantic Web for GIS Practitioners
Introduction to Semantic Web for GIS Practitioners
Emanuele Della Valle
J-P. Fauconnier, J. Roumier. Musonto - A Semantic Search Engine Dedicated to ...
J-P. Fauconnier, J. Roumier. Musonto - A Semantic Search Engine Dedicated to ...
MusicNet
Usage of Linked Data: Introduction and Application Scenarios
Usage of Linked Data: Introduction and Application Scenarios
EUCLID project
Mapping, Interlinking and Exposing MusicBrainz as Linked Data
Mapping, Interlinking and Exposing MusicBrainz as Linked Data
Peter Haase
Music Objects to Social Machines
Music Objects to Social Machines
David De Roure
Future of Web 2.0 & The Semantic Web
Future of Web 2.0 & The Semantic Web
is20090
Sonia Pascua IFLA 2018
Sonia Pascua IFLA 2018
Sonia Pascua
Lee Iverson - How does the web connect content?
Lee Iverson - How does the web connect content?
Museums Computer Group
Linked data and Muruca @ COST a32 - Munich
Linked data and Muruca @ COST a32 - Munich
Christian Morbidoni
Semantic Web Landscape 2009
Semantic Web Landscape 2009
LeeFeigenbaum
Semantic Web Good News
Semantic Web Good News
Frank van Harmelen
Developing A Semantic Web Application - ISWC 2008 tutorial
Developing A Semantic Web Application - ISWC 2008 tutorial
Emanuele Della Valle
Aplicaii Web Semantice - Descriere Proiect
Aplicaii Web Semantice - Descriere Proiect
Vlad Posea
Linked Data Publication of Live Music Archives
Linked Data Publication of Live Music Archives
seanb
S. Dixon, C. Mesnage, B. Norton. LinkedBrainz Live
S. Dixon, C. Mesnage, B. Norton. LinkedBrainz Live
MusicNet
Drupal case study: ABC Dig Music
Drupal case study: ABC Dig Music
David Peterson
Realizing a Semantic Web Application - ICWE 2010 Tutorial
Realizing a Semantic Web Application - ICWE 2010 Tutorial
Emanuele Della Valle
Introduction to Fast by Professor Mark Sandler
Introduction to Fast by Professor Mark Sandler
FASTIMPACT
Ontologies for music from a digital library practitioner's perspective
Ontologies for music from a digital library practitioner's perspective
Jenn Riley
Introduction to Semantic Web for GIS Practitioners
Introduction to Semantic Web for GIS Practitioners
Emanuele Della Valle
J-P. Fauconnier, J. Roumier. Musonto - A Semantic Search Engine Dedicated to ...
J-P. Fauconnier, J. Roumier. Musonto - A Semantic Search Engine Dedicated to ...
MusicNet
Usage of Linked Data: Introduction and Application Scenarios
Usage of Linked Data: Introduction and Application Scenarios
EUCLID project
Mapping, Interlinking and Exposing MusicBrainz as Linked Data
Mapping, Interlinking and Exposing MusicBrainz as Linked Data
Peter Haase
Music Objects to Social Machines
Music Objects to Social Machines
David De Roure
Future of Web 2.0 & The Semantic Web
Future of Web 2.0 & The Semantic Web
is20090
Sonia Pascua IFLA 2018
Sonia Pascua IFLA 2018
Sonia Pascua
Lee Iverson - How does the web connect content?
Lee Iverson - How does the web connect content?
Museums Computer Group
Linked data and Muruca @ COST a32 - Munich
Linked data and Muruca @ COST a32 - Munich
Christian Morbidoni
Semantic Web Landscape 2009
Semantic Web Landscape 2009
LeeFeigenbaum

More from Yves Raimond (8)

Time, Context and Causality in Recommender Systems
Time, Context and Causality in Recommender Systems
Yves Raimond
Deep Learning for Recommender Systems
Deep Learning for Recommender Systems
Yves Raimond
Paris ML meetup
Paris ML meetup
Yves Raimond
Spark Meetup @ Netflix, 05/19/2015
Spark Meetup @ Netflix, 05/19/2015
Yves Raimond
Utilisation du Web Semantique pour les sites de la BBC
Yves Raimond
Linked Data on the BBC
Linked Data on the BBC
Yves Raimond
Linked data and applications
Linked data and applications
Yves Raimond
Web of data
Web of data
Yves Raimond
Time, Context and Causality in Recommender Systems
Time, Context and Causality in Recommender Systems
Yves Raimond
Deep Learning for Recommender Systems
Deep Learning for Recommender Systems
Yves Raimond
Paris ML meetup
Paris ML meetup
Yves Raimond
Spark Meetup @ Netflix, 05/19/2015
Spark Meetup @ Netflix, 05/19/2015
Yves Raimond
Utilisation du Web Semantique pour les sites de la BBC
Yves Raimond
Linked Data on the BBC
Linked Data on the BBC
Yves Raimond
Linked data and applications
Linked data and applications
Yves Raimond
Ad

Recently uploaded (20)

Quantum AI: Where Impossible Becomes Probable
Quantum AI: Where Impossible Becomes Probable
Saikat Basu
The Future of Technology: 2025-2125 by Saikat Basu.pdf
The Future of Technology: 2025-2125 by Saikat Basu.pdf
Saikat Basu
Lessons Learned from Developing Secure AI Workflows.pdf
Lessons Learned from Developing Secure AI Workflows.pdf
Priyanka Aash
Quantum AI Discoveries: Fractal Patterns Consciousness and Cyclical Universes
Quantum AI Discoveries: Fractal Patterns Consciousness and Cyclical Universes
Saikat Basu
GenAI Opportunities and Challenges - Where 370 Enterprises Are Focusing Now.pdf
GenAI Opportunities and Challenges - Where 370 Enterprises Are Focusing Now.pdf
Priyanka Aash
Techniques for Automatic Device Identification and Network Assignment.pdf
Techniques for Automatic Device Identification and Network Assignment.pdf
Priyanka Aash
Tech-ASan: Two-stage check for Address Sanitizer - Yixuan Cao.pdf
Tech-ASan: Two-stage check for Address Sanitizer - Yixuan Cao.pdf
caoyixuan2019
"Scaling in space and time with Temporal", Andriy Lupa.pdf
"Scaling in space and time with Temporal", Andriy Lupa.pdf
Fwdays
AI vs Human Writing: Can You Tell the Difference?
AI vs Human Writing: Can You Tell the Difference?
Shashi Sathyanarayana, Ph.D
Security Tips for Enterprise Azure Solutions
Security Tips for Enterprise Azure Solutions
Michele Leroux Bustamante
Using the SQLExecutor for Data Quality Management: aka One man's love for the...
Using the SQLExecutor for Data Quality Management: aka One man's love for the...
Safe Software
Python Conference Singapore - 19 Jun 2025
Python Conference Singapore - 19 Jun 2025
ninefyi
MuleSoft for AgentForce : Topic Center and API Catalog
MuleSoft for AgentForce : Topic Center and API Catalog
shyamraj55
"Database isolation: how we deal with hundreds of direct connections to the d...
"Database isolation: how we deal with hundreds of direct connections to the d...
Fwdays
" How to survive with 1 billion vectors and not sell a kidney: our low-cost c...
" How to survive with 1 billion vectors and not sell a kidney: our low-cost c...
Fwdays
Mastering AI Workflows with FME by Mark Doring
Mastering AI Workflows with FME by Mark Doring
Safe Software
AI VIDEO MAGAZINE - June 2025 - r/aivideo
AI VIDEO MAGAZINE - June 2025 - r/aivideo
1pcity Studios, Inc
CapCut Pro Crack For PC Latest Version {Fully Unlocked} 2025
CapCut Pro Crack For PC Latest Version {Fully Unlocked} 2025
pcprocore
A Constitutional Quagmire - Ethical Minefields of AI, Cyber, and Privacy.pdf
A Constitutional Quagmire - Ethical Minefields of AI, Cyber, and Privacy.pdf
Priyanka Aash
Raman Bhaumik - Passionate Tech Enthusiast
Raman Bhaumik - Passionate Tech Enthusiast
Raman Bhaumik
Quantum AI: Where Impossible Becomes Probable
Quantum AI: Where Impossible Becomes Probable
Saikat Basu
The Future of Technology: 2025-2125 by Saikat Basu.pdf
The Future of Technology: 2025-2125 by Saikat Basu.pdf
Saikat Basu
Lessons Learned from Developing Secure AI Workflows.pdf
Lessons Learned from Developing Secure AI Workflows.pdf
Priyanka Aash
Quantum AI Discoveries: Fractal Patterns Consciousness and Cyclical Universes
Quantum AI Discoveries: Fractal Patterns Consciousness and Cyclical Universes
Saikat Basu
GenAI Opportunities and Challenges - Where 370 Enterprises Are Focusing Now.pdf
GenAI Opportunities and Challenges - Where 370 Enterprises Are Focusing Now.pdf
Priyanka Aash
Techniques for Automatic Device Identification and Network Assignment.pdf
Techniques for Automatic Device Identification and Network Assignment.pdf
Priyanka Aash
Tech-ASan: Two-stage check for Address Sanitizer - Yixuan Cao.pdf
Tech-ASan: Two-stage check for Address Sanitizer - Yixuan Cao.pdf
caoyixuan2019
"Scaling in space and time with Temporal", Andriy Lupa.pdf
"Scaling in space and time with Temporal", Andriy Lupa.pdf
Fwdays
AI vs Human Writing: Can You Tell the Difference?
AI vs Human Writing: Can You Tell the Difference?
Shashi Sathyanarayana, Ph.D
Security Tips for Enterprise Azure Solutions
Security Tips for Enterprise Azure Solutions
Michele Leroux Bustamante
Using the SQLExecutor for Data Quality Management: aka One man's love for the...
Using the SQLExecutor for Data Quality Management: aka One man's love for the...
Safe Software
Python Conference Singapore - 19 Jun 2025
Python Conference Singapore - 19 Jun 2025
ninefyi
MuleSoft for AgentForce : Topic Center and API Catalog
MuleSoft for AgentForce : Topic Center and API Catalog
shyamraj55
"Database isolation: how we deal with hundreds of direct connections to the d...
"Database isolation: how we deal with hundreds of direct connections to the d...
Fwdays
" How to survive with 1 billion vectors and not sell a kidney: our low-cost c...
" How to survive with 1 billion vectors and not sell a kidney: our low-cost c...
Fwdays
Mastering AI Workflows with FME by Mark Doring
Mastering AI Workflows with FME by Mark Doring
Safe Software
AI VIDEO MAGAZINE - June 2025 - r/aivideo
AI VIDEO MAGAZINE - June 2025 - r/aivideo
1pcity Studios, Inc
CapCut Pro Crack For PC Latest Version {Fully Unlocked} 2025
CapCut Pro Crack For PC Latest Version {Fully Unlocked} 2025
pcprocore
A Constitutional Quagmire - Ethical Minefields of AI, Cyber, and Privacy.pdf
A Constitutional Quagmire - Ethical Minefields of AI, Cyber, and Privacy.pdf
Priyanka Aash
Raman Bhaumik - Passionate Tech Enthusiast
Raman Bhaumik - Passionate Tech Enthusiast
Raman Bhaumik
Ad

Towards a musical Semantic Web

  • 1. Towards a musical Semantic Web Yves Raimond Centre for Digital Music, Queen Mary, University of London May 6th, 2007
  • 2. Overview Introduction Web Web of data The Semantic Web RDF Making sense of the data Content negotiation The Music Ontology The Timeline ontology The Event ontology FRBR + FOAF Music production specific concepts Workflow information Levels of expressiveness Extensions And now?? Linking open data on the Semantic Web Two applications
  • 3. Introduction Web 1. I ask my favourite search engine for Lonah creative commons song Looking for Creative Commons-licensed song from the French band Lonah
  • 4. Introduction Web Looking for Creative Commons-licensed song from the French band Lonah 2. I read the context 油of each of the first results 3. The second one seems ok... 4. I reach this last.fm page: 5. According to the tags, it looks like the band I am looking for... 6. I read Music available on ... and decide to visit the linked page 7. I reach the Jamendo website 8. I launch a search for Lonah , and, finally:
  • 5. Introduction Web Now: Ask your computer to do the same thing! Some requirements emerging from this scenario: - I need an entry point: the search engine - I need to understand the context of the links - I need to find my way into the web maze
  • 6. Introduction Web of data Turning the Web into a huge, semantic, democratic database in order to make machines able to look by themselves for particular informations KB1 KB2 KB3 KB4 Application1 Application 2
  • 7. The Semantic Web Resources on the Web can be far more than just web pages! http://moustaki.org/foaf.rdf#moustaki is a resource representing me http://dbtune.org/jamendo/band/lonah is a resource representing the band Lonah When HTTP-GET ting, Let's leave fancy HTML pages for humans, and let's provide some useful descriptions for the machine! Resource Description Framework http://dbtune.org/jamendo/band/both http://dbtune.org/jamendo/artist/5 Both http://xmlns.com/foaf/0.1/Group
  • 8. Ontologies - Making sense of the data Ontologies , to map these resources and properties (links) 油to real-world objects and relationships Providing a COMMON UNDERSTANDING An Album 油has several Tracks , a name , a release date ... A Performance 油has one location , one time , some performers , ... Ontologies are also described in RDF Instance data refers to ontologies through RDF triples such as: < http://dbtune.org/jamendo/artist/5 > rdf:type < http://purl.org/ontology/mo/Musicartist > < http://dbtune.org/jamendo/artist/5 > foaf:name Both
  • 9. Content negotiation http://dbtune.org/jamendo/artist/5 <mo:MusicArtist rdf:about=&quot;http://dbtune.org/jamendo/artist/5&quot;> <foaf:based_near rdf:resource=&quot;http://dbpedia.org/France&quot;/> <foaf:homepage rdf:resource=&quot;http://www.both-world.com&quot;/> <foaf:img rdf:resource=&quot;http://img.jamendo.com/artists/b/both.jpg&quot;/> <foaf:name rdf:datatype=&quot;&xsd;string&quot;>Both</foaf:name> </mo:MusicArtist> HTML for human consumption RDF for machine consumption And now, let's make both the human 油and the machine happy!
  • 10. The Music Ontology Problem: no agreed ways of dealing with music-related information on the Semantic Web Solution: Let's launch a community project, based on previous ontology engineering efforts! http://musicontology.com/ Several facets [Pachet]: Complex editorial information Acoustic information ( cultural information)
  • 11. The Timeline ontology First thing to address: representing temporal information This performance happened the 9 th of March, 1984 This beat is occurring around sample 32480 The second verse is just before the second chorus ... Only four concepts: Instant , Interval , TimeLine (and TimeLineMap )
  • 12. The Event ontology We need a way to classify space/time regions : Performances, recordings, beats, verses, composition, ...
  • 13. FRBR + FOAF FRBR: Functional Requirements for Bibliographic Records We use three FRBR concepts: Work Manifestation Item The Expression concept seemed to fuzzy for being used: whole workflow between a work and its manifestation FOAF: Friend-of-a-friend Person Group Organization ... and the relationship vocabulary (married, brother of, etc.)
  • 14. Music production specific concepts On top of FRBR: MusicalWork , MusicalManifestation ( Album , Track , Playlist, etc.) MusicalItem ( Stream , a particular Vynil , etc.) On top of FOAF: MusicArtist and MusicGroup (defined classes) Arranger , Engineer , Performer , Composer , etc. (same thing) On top of the Event ontology: Composition , Arrangement , Performance , Sound , Recording Others: Signal , Score , Genre , Instrument , etc.
  • 16. Levels of expressiveness Flexibility of the ontolog y - Level 1: purely editorial This track is on that particular album and that compilation and was created by that artist - Level 2: introducing events This is a recording of this particular musician playing that jazz-rock arrangement of that particular piece - Level 3: introducing event decomposition In this performance, this key was played at this particular time by this person, who was playing the piano
  • 17. Extensions Lots of anchor points (instrument, genre, signal, timeline, etc.) Already several extensions available: - Musical feature ontology : uses Event as a way to classify features on a signal' timeline - Instrument taxonomy : thanks to Musicbrainz! - Genre taxonomy : thanks to Wikipedia/DBPedia - The Key ontology Other possible extensions: - Audio recording devices under the Recording concept? - Mixing events dealing with Signal objects? - Sound cognition under the Sound / Listener concepts? - Symbolic music notation under Score ? - Chord ontology?
  • 18. Linking open data on the Semantic Web W3C' Semantic Web Education and Outreach community project Lots of open data available: Wikipedia, Geonames, Musicbrainz, creative commons repositories, etc. Let's interlink them using Semantic Web technologies: DATA MASHUPS So far: - Jamendo - Magnatune - Musicbrainz - DBPedia - GeoNames - RDF book mashup - ...
  • 19. And now?? - Your audio files are just other items of a particular manifestation , which has an URI - Store the corresponding statements in your SW-enabled application - And your collection gets access to the whole web of knowledge (well, in its current state:-) ) Give me all musical works composed in a city with more than 500 000 inhabitants Is there someone nearby really liking this band and the same beer as me, so that we can have a drink tomorrow? 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 Give me all Jimmy Hendrix songs played by Brass Bands with at least 5 members Are there any other performances of this work? Give me one with a small part at 120 bpm