ontologies*in*the*time*of*linked*data · ontologies*in*the*time*of*linked*data * * *...
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Ontologies in the Time of Linked Data
Hilary Thorsen, Stanford University Cris<na Pa>uelli, Pra> Ins<tute
NASKO 2015 June 19, 2015
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Overview
• Applica<on scenario: Linked Jazz • Bird’s eye view of Linked Open Data • Ontology Building Methodology
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Project Goals Iden<fy the network of rela<onships among jazz ar<sts described in interview transcripts
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Billy Strayhorn composer of Take the "A" Train
predicate subject object
RDF Triples
<http://dbpedia.org/resource/Billy_Strayhorn><http://purl.org/ontology/mo/composer> <http://dbpedia.org/resource/Take_the_%22A%22_Train>
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Knowledge Representa<on Languages
• RDF Schema (RDFS)
• Web Ontology Language (OWL)
• Simple Knowledge Organiza<on System (SKOS)
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Knowledge Representa<on Languages
RDF Schema (RDFS) • Defines classes and proper<es • Organizes them hierarchically
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Knowledge Representa<on Languages
Web Ontology Language (OWL) • Built on RDF and RDFS, but capable of represen<ng complex rela<onships
• Logical combina<on of classes—intersec<ons, unions, and complements
• Axioms on proper<es—transi<ve, symmetric, func<onal, inverse
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Knowledge Representa<on Languages
Simple Knowledge Organiza?on System (SKOS) • OWL ontology • Describes name authori<es with skos:prefLabel and skos:altLabel
• Supports data mapping with skos:exactMatch, skos:closeMatch
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Methodology
Six phases • Specifica<on • Modeling • Genera<on • Linking • Publica<on • Exploita<on
(Vila-‐Suero et al., 2014; Heath and Bizer, 2011; Villazón-‐Terrazas et al., 2011)
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Purpose • A model to describe the datasets created within the project
Scope • Domain of jazz music • Originally limited to jazz ar<sts and social rela<onships
• Now includes music-‐related data (performances, discographies, etc.)
Specifica<on
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Best prac<ce URI path: hCp://(domain)/(type)/(concept)/(reference) Linked Jazz Ontology Namespace: hCp://linkedjazz.org/ontology Example Linked Jazz Ontology URI: hCp://linkedjazz.org/ontology/playedTogether
Specifica<on
Linked Jazz Ontology Namespace
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Criteria • Usage • Maintenance and Governance • Coverage • Expressivity
Vocabulary Selec<on Modeling
Linked Open Vocabularies
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Source Vocabularies
Modeling
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Core set of classes and proper<es for “person” en<ty
Modeling
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h>p://linkedjazz.org/resource/Sam_Rivers
h>p://linkedjazz.org/resource/Charlie_Parker
h>p://linkedjazz.org/resource/Dizzie_Gillespie
h>p://linkedjazz.org/resource/Coleman_Hawkins
h>p://linkedjazz.org/resource/Miles_Davis rel:knowsOf
rel:knowsOf
rel:knowsOf rel:knowsOf
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52nd Street Crowdsourcing Tool
Modeling
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Linked Jazz 52nd Street Rela<onships
Modeling
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Modeling
“Person” en?ty with rela?onship proper?es
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• lj:playedTogether • lj:touredWith • lj:inBandWith • lj:bandLeaderOf • lj:bandMemberOf
Modeling
Linked Jazz Minted Predicates
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Enriched “person” en<ty classes and proper<es
Modeling
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Tree view of the expanded model in Protégé
Modeling
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Expanding the Ontology
Modeling
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Genera<on
Data Mapping
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<http://linkedjazz.org/resource/Sam_Rivers> <owl:sameAs>
<http://dbpedia.org/resource/Sam_Rivers> <owl:sameAs> <http://viaf.org/viaf/164803380/>
<owl:sameAs> <https://musicbrainz.org/artist/f86342be-eef7-445b-
90c9-250bdf3f0b3b>
owl:sameAs
Linking
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<http://linkedjazz.org/resource/Sam_Rivers> <owl:sameAs> <http://dbpedia.org/resource/Sam_Rivers> <owl:sameAs> <http://viaf.org/viaf/164803380/> <owl:sameAs> <https://musicbrainz.org/artist/f86342be-eef7-445b- 90c9-250bdf3f0b3b>
owl:sameAs
Linking
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<http://xmlns.com/foaf/spec/#term_Person> <owl:equivalentClass> <http://schema.org/Person> <owl:equivalentClass> <http://dbpedia.org/ontology/Person>
Owl:equivalentClass
Linking
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<http://xmlns.com/foaf/spec/#term_member> <owl:equivalentProperty> <http://purl.org/ontology/mo/member>
owl:equivalentProperty
Linking
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Publica<on
LodView page for Sam Rivers
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Exploita<on
SPARQL Query to return Sam River’s rela<onships
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Tradi<onal vs. LOD Ontologies
• Specifica<on • Modeling • Genera<on • Linking • Publica?on • Exploita<on
• Lightweight, open structure • Built from the bo>om up with
extensions and adjustments • Easy reuse of terms through
mixing and mapping
• Specifica<on • Modeling • Genera<on
• Exploita<on • Structure can be complex
with strict logical formalisms • Terms created to capture
en<re domain of interest • Difficult to reuse