SlideShare a Scribd company logo
Towards a musical Semantic Web Yves Raimond Centre for Digital Music, Queen Mary, University of London May 6th, 2007
Overview ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
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  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)  to  real-world objects and  relationships Providing a COMMON UNDERSTANDING An  Album  has several  Tracks , a  name , a  release date ... A  Performance  has one  location , one  time , some  performers , ... ,[object Object],[object Object],[object Object],[object Object]
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   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/ ,[object Object],[object Object],[object Object],[object Object]
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 ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],FOAF: Friend-of-a-friend ,[object Object],[object Object],[object Object],[object Object]
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!!

More Related Content

Similar to Towards a musical Semantic Web

Jewish Music Online: Digital Fieldwork
Jewish Music Online: Digital FieldworkJewish Music Online: Digital Fieldwork
Jewish Music Online: Digital Fieldwork
Francesco Spagnolo
 
The Streams of Our Lives - Visualizing Listening Histories in Context
The Streams of Our Lives - Visualizing Listening Histories in ContextThe Streams of Our Lives - Visualizing Listening Histories in Context
The Streams of Our Lives - Visualizing Listening Histories in Context
Dominikus Baur
 
Enhancing a Digital Sheet Music Collection A report for LIS-435 ...
 Enhancing a Digital Sheet Music Collection A report for LIS-435 ... Enhancing a Digital Sheet Music Collection A report for LIS-435 ...
Enhancing a Digital Sheet Music Collection A report for LIS-435 ...crysatal16
 
Notes
NotesNotes
J-P. Fauconnier, J. Roumier. Musonto - A Semantic Search Engine Dedicated to ...
J-P. Fauconnier, J. Roumier. Musonto - A Semantic Search Engine Dedicated to ...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
 
Aplicații Web Semantice - Descriere Proiect
Aplicații Web Semantice - Descriere ProiectAplicații Web Semantice - Descriere Proiect
Aplicații Web Semantice - Descriere ProiectVlad Posea
 
Introduction to Music Information Retrieval
Introduction to Music Information RetrievalIntroduction to Music Information Retrieval
Introduction to Music Information Retrieval
Sease
 
Introduction to Music Information Retrieval
Introduction to Music Information RetrievalIntroduction to Music Information Retrieval
Introduction to Music Information Retrieval
Andrea Gazzarini
 
Denktank 2010
Denktank 2010Denktank 2010
Denktank 2010
ocor203
 
MongoDB at ex.fm
MongoDB at ex.fmMongoDB at ex.fm
MongoDB at ex.fmMongoDB
 
Sonia Pascua IFLA 2018
Sonia Pascua IFLA 2018Sonia Pascua IFLA 2018
Sonia Pascua IFLA 2018
Sonia Pascua
 
Music Personalization At Spotify
Music Personalization At SpotifyMusic Personalization At Spotify
Music Personalization At Spotify
Vidhya Murali
 
Linked Open Europeana: Semantics for the Citizen
Linked Open Europeana: Semantics for the CitizenLinked Open Europeana: Semantics for the Citizen
Linked Open Europeana: Semantics for the CitizenStefan Gradmann
 
Stop Looking and Start Listening
Stop Looking and Start ListeningStop Looking and Start Listening
Stop Looking and Start ListeningBecky Stewart
 
Linked Data Publication of Live Music Archives and Analyses
Linked Data Publication of Live Music Archives and AnalysesLinked Data Publication of Live Music Archives and Analyses
Linked Data Publication of Live Music Archives and Analyses
seanb
 
楊奕軒/音樂資料檢索
楊奕軒/音樂資料檢索楊奕軒/音樂資料檢索
楊奕軒/音樂資料檢索
台灣資料科學年會
 
Knowledge-based Music Recommendation
Knowledge-based Music RecommendationKnowledge-based Music Recommendation
Knowledge-based Music Recommendation
Pasquale Lisena
 
Share The Music - Introduction
Share The Music - IntroductionShare The Music - Introduction
Share The Music - Introduction
ShareTheMusic
 

Similar to Towards a musical Semantic Web (20)

Jewish Music Online: Digital Fieldwork
Jewish Music Online: Digital FieldworkJewish Music Online: Digital Fieldwork
Jewish Music Online: Digital Fieldwork
 
Music mobile
Music mobileMusic mobile
Music mobile
 
The Streams of Our Lives - Visualizing Listening Histories in Context
The Streams of Our Lives - Visualizing Listening Histories in ContextThe Streams of Our Lives - Visualizing Listening Histories in Context
The Streams of Our Lives - Visualizing Listening Histories in Context
 
Enhancing a Digital Sheet Music Collection A report for LIS-435 ...
 Enhancing a Digital Sheet Music Collection A report for LIS-435 ... Enhancing a Digital Sheet Music Collection A report for LIS-435 ...
Enhancing a Digital Sheet Music Collection A report for LIS-435 ...
 
Notes
NotesNotes
Notes
 
J-P. Fauconnier, J. Roumier. Musonto - A Semantic Search Engine Dedicated to ...
J-P. Fauconnier, J. Roumier. Musonto - A Semantic Search Engine Dedicated to ...J-P. Fauconnier, J. Roumier. Musonto - A Semantic Search Engine Dedicated to ...
J-P. Fauconnier, J. Roumier. Musonto - A Semantic Search Engine Dedicated to ...
 
Aplicații Web Semantice - Descriere Proiect
Aplicații Web Semantice - Descriere ProiectAplicații Web Semantice - Descriere Proiect
Aplicații Web Semantice - Descriere Proiect
 
Introduction to Music Information Retrieval
Introduction to Music Information RetrievalIntroduction to Music Information Retrieval
Introduction to Music Information Retrieval
 
Introduction to Music Information Retrieval
Introduction to Music Information RetrievalIntroduction to Music Information Retrieval
Introduction to Music Information Retrieval
 
Ism2011
Ism2011Ism2011
Ism2011
 
Denktank 2010
Denktank 2010Denktank 2010
Denktank 2010
 
MongoDB at ex.fm
MongoDB at ex.fmMongoDB at ex.fm
MongoDB at ex.fm
 
Sonia Pascua IFLA 2018
Sonia Pascua IFLA 2018Sonia Pascua IFLA 2018
Sonia Pascua IFLA 2018
 
Music Personalization At Spotify
Music Personalization At SpotifyMusic Personalization At Spotify
Music Personalization At Spotify
 
Linked Open Europeana: Semantics for the Citizen
Linked Open Europeana: Semantics for the CitizenLinked Open Europeana: Semantics for the Citizen
Linked Open Europeana: Semantics for the Citizen
 
Stop Looking and Start Listening
Stop Looking and Start ListeningStop Looking and Start Listening
Stop Looking and Start Listening
 
Linked Data Publication of Live Music Archives and Analyses
Linked Data Publication of Live Music Archives and AnalysesLinked Data Publication of Live Music Archives and Analyses
Linked Data Publication of Live Music Archives and Analyses
 
楊奕軒/音樂資料檢索
楊奕軒/音樂資料檢索楊奕軒/音樂資料檢索
楊奕軒/音樂資料檢索
 
Knowledge-based Music Recommendation
Knowledge-based Music RecommendationKnowledge-based Music Recommendation
Knowledge-based Music Recommendation
 
Share The Music - Introduction
Share The Music - IntroductionShare The Music - Introduction
Share The Music - Introduction
 

More from Yves Raimond

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

More from Yves Raimond (8)

Time, Context and Causality in Recommender Systems
Time, Context and Causality in Recommender SystemsTime, Context and Causality in Recommender Systems
Time, Context and Causality in Recommender Systems
 
Deep Learning for Recommender Systems
Deep Learning for Recommender SystemsDeep Learning for Recommender Systems
Deep Learning for Recommender Systems
 
Paris ML meetup
Paris ML meetupParis ML meetup
Paris ML meetup
 
Spark Meetup @ Netflix, 05/19/2015
Spark Meetup @ Netflix, 05/19/2015Spark Meetup @ Netflix, 05/19/2015
Spark Meetup @ Netflix, 05/19/2015
 
Utilisation du Web Semantique pour les sites de la BBC
Utilisation du Web Semantique pour les sites de la BBCUtilisation du Web Semantique pour les sites de la BBC
Utilisation du Web Semantique pour les sites de la BBC
 
Linked Data on the BBC
Linked Data on the BBCLinked Data on the BBC
Linked Data on the BBC
 
Linked data and applications
Linked data and applicationsLinked data and applications
Linked data and applications
 
Web of data
Web of dataWeb of data
Web of data
 

Recently uploaded

Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdfSmart TV Buyer Insights Survey 2024 by 91mobiles.pdf
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf
91mobiles
 
The Future of Platform Engineering
The Future of Platform EngineeringThe Future of Platform Engineering
The Future of Platform Engineering
Jemma Hussein Allen
 
FIDO Alliance Osaka Seminar: The WebAuthn API and Discoverable Credentials.pdf
FIDO Alliance Osaka Seminar: The WebAuthn API and Discoverable Credentials.pdfFIDO Alliance Osaka Seminar: The WebAuthn API and Discoverable Credentials.pdf
FIDO Alliance Osaka Seminar: The WebAuthn API and Discoverable Credentials.pdf
FIDO Alliance
 
FIDO Alliance Osaka Seminar: Overview.pdf
FIDO Alliance Osaka Seminar: Overview.pdfFIDO Alliance Osaka Seminar: Overview.pdf
FIDO Alliance Osaka Seminar: Overview.pdf
FIDO Alliance
 
FIDO Alliance Osaka Seminar: Passkeys at Amazon.pdf
FIDO Alliance Osaka Seminar: Passkeys at Amazon.pdfFIDO Alliance Osaka Seminar: Passkeys at Amazon.pdf
FIDO Alliance Osaka Seminar: Passkeys at Amazon.pdf
FIDO Alliance
 
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Encryption in Microsoft 365 - ExpertsLive Netherlands 2024
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024
Albert Hoitingh
 
Leading Change strategies and insights for effective change management pdf 1.pdf
Leading Change strategies and insights for effective change management pdf 1.pdfLeading Change strategies and insights for effective change management pdf 1.pdf
Leading Change strategies and insights for effective change management pdf 1.pdf
OnBoard
 
From Siloed Products to Connected Ecosystem: Building a Sustainable and Scala...
From Siloed Products to Connected Ecosystem: Building a Sustainable and Scala...From Siloed Products to Connected Ecosystem: Building a Sustainable and Scala...
From Siloed Products to Connected Ecosystem: Building a Sustainable and Scala...
Product School
 
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024
Tobias Schneck
 
FIDO Alliance Osaka Seminar: FIDO Security Aspects.pdf
FIDO Alliance Osaka Seminar: FIDO Security Aspects.pdfFIDO Alliance Osaka Seminar: FIDO Security Aspects.pdf
FIDO Alliance Osaka Seminar: FIDO Security Aspects.pdf
FIDO Alliance
 
De-mystifying Zero to One: Design Informed Techniques for Greenfield Innovati...
De-mystifying Zero to One: Design Informed Techniques for Greenfield Innovati...De-mystifying Zero to One: Design Informed Techniques for Greenfield Innovati...
De-mystifying Zero to One: Design Informed Techniques for Greenfield Innovati...
Product School
 
UiPath Test Automation using UiPath Test Suite series, part 4
UiPath Test Automation using UiPath Test Suite series, part 4UiPath Test Automation using UiPath Test Suite series, part 4
UiPath Test Automation using UiPath Test Suite series, part 4
DianaGray10
 
Essentials of Automations: Optimizing FME Workflows with Parameters
Essentials of Automations: Optimizing FME Workflows with ParametersEssentials of Automations: Optimizing FME Workflows with Parameters
Essentials of Automations: Optimizing FME Workflows with Parameters
Safe Software
 
State of ICS and IoT Cyber Threat Landscape Report 2024 preview
State of ICS and IoT Cyber Threat Landscape Report 2024 previewState of ICS and IoT Cyber Threat Landscape Report 2024 preview
State of ICS and IoT Cyber Threat Landscape Report 2024 preview
Prayukth K V
 
AI for Every Business: Unlocking Your Product's Universal Potential by VP of ...
AI for Every Business: Unlocking Your Product's Universal Potential by VP of ...AI for Every Business: Unlocking Your Product's Universal Potential by VP of ...
AI for Every Business: Unlocking Your Product's Universal Potential by VP of ...
Product School
 
GraphRAG is All You need? LLM & Knowledge Graph
GraphRAG is All You need? LLM & Knowledge GraphGraphRAG is All You need? LLM & Knowledge Graph
GraphRAG is All You need? LLM & Knowledge Graph
Guy Korland
 
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...
DanBrown980551
 
UiPath Test Automation using UiPath Test Suite series, part 3
UiPath Test Automation using UiPath Test Suite series, part 3UiPath Test Automation using UiPath Test Suite series, part 3
UiPath Test Automation using UiPath Test Suite series, part 3
DianaGray10
 
PCI PIN Basics Webinar from the Controlcase Team
PCI PIN Basics Webinar from the Controlcase TeamPCI PIN Basics Webinar from the Controlcase Team
PCI PIN Basics Webinar from the Controlcase Team
ControlCase
 
FIDO Alliance Osaka Seminar: Passkeys and the Road Ahead.pdf
FIDO Alliance Osaka Seminar: Passkeys and the Road Ahead.pdfFIDO Alliance Osaka Seminar: Passkeys and the Road Ahead.pdf
FIDO Alliance Osaka Seminar: Passkeys and the Road Ahead.pdf
FIDO Alliance
 

Recently uploaded (20)

Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdfSmart TV Buyer Insights Survey 2024 by 91mobiles.pdf
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf
 
The Future of Platform Engineering
The Future of Platform EngineeringThe Future of Platform Engineering
The Future of Platform Engineering
 
FIDO Alliance Osaka Seminar: The WebAuthn API and Discoverable Credentials.pdf
FIDO Alliance Osaka Seminar: The WebAuthn API and Discoverable Credentials.pdfFIDO Alliance Osaka Seminar: The WebAuthn API and Discoverable Credentials.pdf
FIDO Alliance Osaka Seminar: The WebAuthn API and Discoverable Credentials.pdf
 
FIDO Alliance Osaka Seminar: Overview.pdf
FIDO Alliance Osaka Seminar: Overview.pdfFIDO Alliance Osaka Seminar: Overview.pdf
FIDO Alliance Osaka Seminar: Overview.pdf
 
FIDO Alliance Osaka Seminar: Passkeys at Amazon.pdf
FIDO Alliance Osaka Seminar: Passkeys at Amazon.pdfFIDO Alliance Osaka Seminar: Passkeys at Amazon.pdf
FIDO Alliance Osaka Seminar: Passkeys at Amazon.pdf
 
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Encryption in Microsoft 365 - ExpertsLive Netherlands 2024
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024
 
Leading Change strategies and insights for effective change management pdf 1.pdf
Leading Change strategies and insights for effective change management pdf 1.pdfLeading Change strategies and insights for effective change management pdf 1.pdf
Leading Change strategies and insights for effective change management pdf 1.pdf
 
From Siloed Products to Connected Ecosystem: Building a Sustainable and Scala...
From Siloed Products to Connected Ecosystem: Building a Sustainable and Scala...From Siloed Products to Connected Ecosystem: Building a Sustainable and Scala...
From Siloed Products to Connected Ecosystem: Building a Sustainable and Scala...
 
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024
 
FIDO Alliance Osaka Seminar: FIDO Security Aspects.pdf
FIDO Alliance Osaka Seminar: FIDO Security Aspects.pdfFIDO Alliance Osaka Seminar: FIDO Security Aspects.pdf
FIDO Alliance Osaka Seminar: FIDO Security Aspects.pdf
 
De-mystifying Zero to One: Design Informed Techniques for Greenfield Innovati...
De-mystifying Zero to One: Design Informed Techniques for Greenfield Innovati...De-mystifying Zero to One: Design Informed Techniques for Greenfield Innovati...
De-mystifying Zero to One: Design Informed Techniques for Greenfield Innovati...
 
UiPath Test Automation using UiPath Test Suite series, part 4
UiPath Test Automation using UiPath Test Suite series, part 4UiPath Test Automation using UiPath Test Suite series, part 4
UiPath Test Automation using UiPath Test Suite series, part 4
 
Essentials of Automations: Optimizing FME Workflows with Parameters
Essentials of Automations: Optimizing FME Workflows with ParametersEssentials of Automations: Optimizing FME Workflows with Parameters
Essentials of Automations: Optimizing FME Workflows with Parameters
 
State of ICS and IoT Cyber Threat Landscape Report 2024 preview
State of ICS and IoT Cyber Threat Landscape Report 2024 previewState of ICS and IoT Cyber Threat Landscape Report 2024 preview
State of ICS and IoT Cyber Threat Landscape Report 2024 preview
 
AI for Every Business: Unlocking Your Product's Universal Potential by VP of ...
AI for Every Business: Unlocking Your Product's Universal Potential by VP of ...AI for Every Business: Unlocking Your Product's Universal Potential by VP of ...
AI for Every Business: Unlocking Your Product's Universal Potential by VP of ...
 
GraphRAG is All You need? LLM & Knowledge Graph
GraphRAG is All You need? LLM & Knowledge GraphGraphRAG is All You need? LLM & Knowledge Graph
GraphRAG is All You need? LLM & Knowledge Graph
 
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...
 
UiPath Test Automation using UiPath Test Suite series, part 3
UiPath Test Automation using UiPath Test Suite series, part 3UiPath Test Automation using UiPath Test Suite series, part 3
UiPath Test Automation using UiPath Test Suite series, part 3
 
PCI PIN Basics Webinar from the Controlcase Team
PCI PIN Basics Webinar from the Controlcase TeamPCI PIN Basics Webinar from the Controlcase Team
PCI PIN Basics Webinar from the Controlcase Team
 
FIDO Alliance Osaka Seminar: Passkeys and the Road Ahead.pdf
FIDO Alliance Osaka Seminar: Passkeys and the Road Ahead.pdfFIDO Alliance Osaka Seminar: Passkeys and the Road Ahead.pdf
FIDO Alliance Osaka Seminar: Passkeys and the Road Ahead.pdf
 

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.
  • 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  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.
  • 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  and the machine happy!
  • 10.
  • 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.
  • 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