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Mapping, Interlinking and Exposing MusicBrainz as Linked Data 1st Interna*onal Workshop on Seman*c Music and Media (SMAM2013) Sydney, Oct 21, 2013 Peter Haase
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What this talk is about A Linked Data Perspec=ve
affiliation affiliation (previous)
participatesIn participatesIn
isAbout
publishedTo
builtWith
worksOn
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EUCLID: EdUca=onal Curriculum for the usage of LinkedData
@euclid_project euclidproject euclidproject
http://www.euclid-project.eu
Other channels
eBook Course
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EUCLID Scenario
Visualiza*on Module
Metadata Streaming providers
Physical Wrapper
Downloads
Dat
a ac
quis
ition
R2R Transf. LD Wrapper
Musical Content
App
licat
ion
Analysis & Mining Module
LD D
atas
et
Acc
ess
LD Wrapper
RDF/ XML
Integrated Dataset
Interlinking Cleansing Vocabulary Mapping
SPARQL Endpoint
Publishing
RDFa
Other content
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MusicBrainz
• MusicBrainz is an open music encyclopedia that collects music metadata and makes it available to the public.
• MusicBrainz aims to be: • The ul=mate source of music informa=on by allowing anyone to contribute and releasing the data under open licenses. • The universal lingua franca for music by providing a reliable and unambiguous form of music iden*fica*on, enabling both people and machines to have meaningful conversa*ons about music.
• Like Wikipedia, MusicBrainz is maintained by a global community of users and we want everyone — including you — to par*cipate and contribute.
• MusicBrainz is operated by the MetaBrainz Founda*on, dedicated to keeping MusicBrainz free and open source.
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Publishing Rela=onal Databases as RDF: W3C RDB2RDF
Task: Publish data from rela*onal DBMS as Linked Data
Approach: map from
rela*onal schema to seman*c vocabulary with R2RML
Publishing: two alterna*ves –
• Translate SPARQL into SQL on the fly
• Batch transform data into RDF, infer, index , integrate and provide SPARQL access in a triplestore
LD Dataset
Access
Integrated Data in
Triplestore
Interlinking Cleansing Vocabulary Mapping
SPARQL Endpoint
Publishing
Data acquisi*
on
R2RML Engine
Rela*onal DBMS
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Publishing MusicBrainz
Music Ontology MusicBrainz DB R2RML
h"ps://wiki.musicbrainz.org/Next_Genera;on_Schema h"p://musicontology.com
Table Recording(gid, length) Ontology concept mo:recording R2RML Mapping
Concrete Example Mapping
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MusicBrainz Next Gen Schema ar=st As pre-‐NGS, but
further a`ributes
ar=st_credit Allows joint credit
release_group Cf. ‘album’
versus:
release medium
• track • tracklist
• work • recording
https://wiki.musicbrainz.org/Next_Generation_Schema
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Music Ontology OWL ontology with following core concepts (classes) and
rela*onships (proper*es):
Source: http://musicontology.com
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R2RML Class Mapping Mapping tables to classes is ‘easy’: lb:Artist a rr:TriplesMap ; rr:logicalTable [rr:tableName "artist"] ; rr:subjectMap [rr:class mo:MusicArtist ; rr:template "http://musicbrainz.org/artist/{gid}#_"] ; rr:predicateObjectMap [rr:predicate mo:musicbrainz_guid ; rr:objectMap [rr:column "gid" ; rr:datatype xsd:string]] .
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R2RML Property Mapping Mapping columns to proper*es can be easy: lb:artist_name a rr:TriplesMap ; rr:logicalTable [rr:sqlQuery """SELECT artist.gid, artist_name.name FROM artist INNER JOIN artist_name ON artist.name =
artist_name.id"""] ; rr:subjectMap [rr:template "http://musicbrainz.org/artist/{gid}#_"] ; rr:predicateObjectMap [rr:predicate foaf:name ; rr:objectMap [rr:column "name"]] .
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NGS Advanced Rela=ons Major en**es (Ar*st, Release Group, Track, etc.) plus URL
are paired (l_ar*st_ar*st)
Each pairing of instances refers to a Link
Links have types (cf. RDF proper*es) and a`ributes
http://wiki.musicbrainz.org/Advanced_Relationship
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R2RML Mapping Editor
Rela*onal Database
R2RML Mappings
R2RML Engine SPARQL Endpoint
R2RML: Expose data from relational DBMS as RDF / via SPARQL Endpoint
R2RML Edi*ng Made Easy! Hides vocabulary intricacies from end-‐user
Access to metadata about rela*onal databases
Preview of generated triples and SQL queries
Very expressive (Supports most of R2RML)
Problem: R2RML Mappings are hard to create
See our R2RML Mapping Editor in the ISWC Demo Session on Wednesday!
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Scale MusicBrainz RDF derived via R2RML:
lb:artist_member a rr:TriplesMap ; rr:logicalTable [rr:sqlQuery """SELECT a1.gid, a2.gid AS band FROM artist a1 INNER JOIN l_artist_artist ON a1.id = l_artist_artist.entity0 INNER JOIN link ON l_artist_artist.link = link.id INNER JOIN link_type ON link_type = link_type.id INNER JOIN artist a2 on l_artist_artist.entity1 = a2.id WHERE link_type.gid='5be4c609-‐9afa-‐4ea0-‐910b-‐12ffb71e3821'"""] ; rr:subjectMap [rr:template "http://musicbrainz.org/artist/{gid}#_"] ; rr:predicateObjectMap [rr:predicate mo:member_of ; rr:objectMap [rr:template "http://musicbrainz.org/artist/{band}#_" ; rr:termType rr:IRI]] .
150M Triples
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Some Sta=s=cs – RDF Dump
(Lead) Table Triples Time (s) area 59798 2 artist 36868228 423 dbpedia 172017 13 label 201832 3 medium 18069143 163 recording 11400354 209 release_group 3050818 31 release 9764887 151 track 75506495 794 work 1728955 20
156822527 1809
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Informa=on Workbench PlaGorm for Linked Data Applica=ons
§ Open standards and technologies
• Seman*c Wiki based frontend (Using SMW Syntax)
• Suppor*ng W3C standards (OWL, RDF, SPARQL,, …)
• Community Edi*on (Open Source) + Enterprise Edi*on (Commercial)
§ Seman*cs-‐ & Linked Data-‐based integra=on of private and public data sources based on data providers
• Generic and specific providers for various data formats and sources
• Supports established mapping frameworks (e.g. R2RML, SILK, …)
• Named graphs for managing contexts and provenance
§ Intelligent Data Access and Analy=cs • Flexible self-‐service UI • Visualiza*on, explora*on,
dashboarding and repor*ng • Seman*c search
§ Collabora=on and knowledge management
• Cura*on & authoring • Collabora*ve workflows
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Data storage and management plajorm
Reusable UI and data integra*on components
Customized applica*on solu*ons
External resources to reuse data and create mashups
Realiza=on within the Informa=on Workbench Architecture
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The “MusicBrainz Explorer” Applica=on
Data
Data Providers
Ontology
Templates
Widgets
Music Ontology
R2RML
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Template: …
Ontology as a “Structural Backbone” Resource page
RDF Data Graph
Ontology (RDFS/OWL)
The_Beatles Yesterday
mo:Ar=st
mo:Track
rdf:type rdf:type
Template:mo:Track
UI templates
Template:mo:Ar=st
Resource page
Defining data
structure
Defining UI
structure
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Information Workbench: Browsing a Music Artist
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Information Workbench: Visualization techniques
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Naviga=on Through the Data
Source: http://musicbrainz.fluidops.net/resource/Analytical5
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SPARQL visualization
SELECT ?release ((SUM(xsd:double(?duration/60000))) AS ?avg) WHERE { <http://dbpedia.org/resource/The_Beatles> foaf:made ?release . ?release mo:record ?record . ?record mo:track ?track . ?track mo:duration ?duration .} GROUP BY ?release ORDER BY DESC(?avg) LIMIT 10
SPARQL Query
Result set
Top ten The Beatles releases according to the sum of track durations in minutes
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SPARQL visualization
Top ten The Beatles releases according to the sum of track durations in minutes Widget
Visualization: Bar chart
{{#widget: BarChart | query ='SELECT (COUNT(?Release) AS ?COUNT) ?label WHERE { <http://musicbrainz.org/artist/8538e728-‐ca0b-‐4321-‐b7e5-‐cff6565dd4c0#_> foaf:made ?Release. ?Release rdf:type mo:Release . ?Release dc:title ?label .} GROUP BY ?label ORDER BY DESC(?COUNT) LIMIT 20' | settings = 'Settings:barvertical_mb' | asynch = 'true' | input = 'label' | output = 'COUNT' | height = '300’}}
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Information Workbench: SPARQL visualization Top ten The Beatles releases according to the sum of track durations in minutes Other visualiza*ons of the same result set …
Line chart:
Pie chart:
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Automated Widget Suggestion
Bar chart
Line chart
Pie chart
1
2 3 Table
Pivot view
Select a suggested visualization Visualization automatically built
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R2RML Mappings • h`ps://github.com/LinkedBrainz/MusicBrainz-‐R2RML
MusicBrainz RDF Dump • h`p://mbsandbox.org/~barry/ MusicBrainz Linked Data Demo system • h`p://musicbrainz.fluidops.net/ Informa*on Workbench • h`p://www.fluidops.com/informa*on-‐workbench/
Euclid Project • h`p://euclid-‐project.eu/
Try it out!
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Acknowledgements The Euclid Project Barry Norton Michael Meier Andriy Nikolov Yves Raimond Kurt Jacobson Thomas Gaengler Juan Sequeda Simon Dixon
(in no par;cular order)
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Contact Peter Haase fluid Opera*ons AG Altro`str. 31 Walldorf Germany +49 (0) 6227 358087-‐0 www.fluidops.com [email protected]
Thank you!