Embedding libraries and cultural memory …LOD resource description • Application Profiles (Dublin...
Transcript of Embedding libraries and cultural memory …LOD resource description • Application Profiles (Dublin...
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Embedding libraries and cultural memory institutions
in the Linked Data cloud
Thomas Baker Dublin Core Metadata Initiative
International Symposium on Knowledge Communities 2012 Research Center for Knowledge Communities
University of Tsukuba 15 December 2012
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Linking Open Data cloud diagram by Richard Cyganiak and Anja Jentzsch http://lod-cloud.net/
Data Web – the Cloud…
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Description of a scientific article...
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Topic of the article Is “acrididae”, i.e. “grasshoppers”.
One author is named “Lu Hui”.
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Triplifying the description…
Subject Predicate Object
agris:CN2009002389 has the Title 典型草原三种蝗虫种群死亡率的研究
agris:CN2009002389 has an Author Lu Hui
agris:CN2009002389 has a Topic Acrididae (grasshoppers)
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Resource A is identified by the URI http://agris.fao.org/resource/CN2009002389. Let’s abbreviate this as agris:CN2009002389.
A URI identifying the article
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Triplifying the description…
Subject Predicate Object
agris:CN2009002389 has the Title 典型草原三种蝗虫种群死亡率的研究
agris:CN2009002389 has an Author agris-author:luhui
agris-author:luhui has the Name Lu Hui
agris:CN2009002389 has a Topic Acrididae (grasshoppers)
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A URI identifying the author
The author is identified by the URI http://agris.fao.org/author/luhui. Let’s abbreviate this as agris-author:luhui.
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Triplifying the description…
Subject Predicate Object
agris:CN2009002389 has the Title 典型草原三种蝗虫种群死亡率的研究
agris:CN2009002389 has an Author agris-author:luhui
agris-author:luhui has the Name Lu Hui
agris:CN2009002389 has a Topic agrovoc:c_4416
agrovoc:c_4416 has preferred label Acrididae (en)
agrovoc:c_4416 has preferred label 蝗科 (zh)
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The description of http://aims.fao.org/aos/agrovoc/c_4416 in the AGROVOC Concept Scheme tells us how this concept is labeled in English and in Chinese.
A URI identifying the subject
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Triplifying the description…
Subject Predicate Object
agris:CN2009002389 dct:title 典型草原三种蝗虫种群死亡率的研究
agris:CN2009002389 dct:creator agris-author:luhui
agris-author:luhui foaf:name Lu Hui
agris:CN2009002389 dct:subject agrovoc:c_4416
agrovoc:c_4416 has preferred label Acrididae (en)
agrovoc:c_4416 has preferred label 蝗科 (zh)
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URIs identifying properties (from Dublin Core and SKOS)
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Triplifying the description…
Subject Predicate Object
agris:CN2009002389 dct:title 典型草原三种蝗虫种群死亡率的研究
agris:CN2009002389 dct:creator agris-author:luhui
agris-author:luhui foaf:name Lu Hui
agris:CN2009002389 dct:subject agrovoc:c_4416
agrovoc:c_4416 skos:prefLabel Acrididae (en)
agrovoc:c_4416 skos:prefLabel 蝗科 (zh)
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URIs identifying properties (from SKOS)
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Triples seen as a graph
Subject Predicate Object
agris:CN2009002389 dct:title 典型草原三种蝗虫种群死亡率的研究
agris:CN2009002389 dct:creator agris-author:luhui
agris-author:luhui foaf:name Lu Hui
agris:CN2009002389 dct:subject agrovoc:c_4416
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agris:CN…389 dct:title
典型草…
Lu Hui
agris-author: luhui
dct:subject
agrovoc:c_4416
foaf:name
dct:creator
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Computers detect URIs that match...
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agris:CN…389 dct:title
典型草…
Lu Hui
agris-author: luhui
dct:subject agrovoc:c_4416
foaf:name
dct:creator
agris:CH…179 dct:title
Heuschrecken
Peter, B.
agris-author: peterb
dct:subject
agrovoc:c_4416 foaf:name
dct:creator
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…thus “linking” the descriptions
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agris:CN…389 dct:title
典型草…
Lu Hui
agris-author: luhui
dct:subject
foaf:name
dct:creator
agris:CH…179 dct:title
Heuschrecken
Peter, B.
agris-author: peterb
dct:subject
agrovoc:c_4416 foaf:name
dct:creator
An infinitely expandable description
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Expanding to other Web resources
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AGRIS record
AGROVOC concept
DBPedia concept
VIVO Expert
BBC Web page
BBC News
Wikipedia page
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“Records” have become clusters of links
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AGRIS record
AGROVOC
AGRIS Authors Dublin Core
FOAF
SKOS
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Traditional IT maps between Records
Schema A Schema B Schema C
same as
mapped to
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Linked Data applications create good triples
Application A Application B Application C
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Linked Data “speaks for itself”...
Application A Application B Application C
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DC Dataset
SKOS
FOAF
LCSH VIAF
Dataset
…as long as source datasets and vocabularies are preserved
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What Linked Data uses URIs for
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Concept
Object
Event
Place
Corporate Body
Person
...and the relationships between them (properties)
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FRBR theory
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Concept
Object
Event
Place
Corporate Body
Person Work
Expression
Manifestation
Item
“WEMI”
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FRBR theory
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can stand alone
must relate to only one Work?
must relate to one or more Expressions?
must relate to only one Manifestation?
Do entities inherit from higher levels?
“WEMI”
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Replacing cataloging rules?
• Resource Description and Access (RDA) – Successor to AACR for library catalogs – Tied to FRBR ontology – Better support for relationships – Implies Work and Expression for every
bibliographic item – Like FRBR, relatively untested
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Replacing MARC format?
• Bibframe Initiative – Library of Congress replacement for MARC – http://www.loc.gov/marc/transition/pdf/marcld-report-11-21-2012.pdf
• Has Work, but model is simpler than WEMI • First draft, November 2012:
– More about data structures than “ontology”? – Like Application Profiles...?
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LOD resource description
• Application Profiles (Dublin Core-style) – Use any syntax mappable to Linked Data – Use any combination of RDF vocabularies – Define “record”-like data packages – From very simple descriptions, to complex,
depending on requirements...
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LOD e-commerce description
• Schema.org – Structured information about People, Hotels,
Recipes, Books, Movies… – Uses RDFa to embed descriptions in Web pages – Indexed by Google, Yahoo… – Oriented more to high-impact e-commerce than
to the “long tail” of scientific and cultural data
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LOD concept description
• W3C Web Ontology Language (OWL) models “reality” to support inference – If Dog is a sub-class Mammal, and “Oscar” is a
Dog, then “Oscar” is a Mammal
• Define a “cartoon universe” (Dogs, Cats, Mammals)
• Can be difficult and expensive to design
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LOD concept description
• SKOS Concept Schemes – W3C Simple Knowledge Organization System – SKOS pragmatically avoids supporting inference – If Car is broader than Wheel, and Machine is
broader than Car, Machine is not “broader than” Wheel
• OWL and SKOS provide URIs for Linked Data – SKOS is easier, often “good enough”
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Making RDF publication easier
Drupal 7 content management Easy workflows help non-experts publish on Web Uses RDFa embedded in Web pages (like
schema.org) Can output other RDF serialization formats
(RDF/XML, Turtle, JSONLD…) Support for SPARQL endpoints
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Simplicity scales better
• Many can agree on small standards (SKOS, DC, RDF)
• A few can agree on large complex standards (FRBR, RDA)
• Rare for many to agree on large complex standards
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Recipe for Interoperability
1. What elements of your data really need to interoperate?
2. Map those parts to a core model. 3. Define the core model using URIs and RDF. 4. Publish the core data elements as Linked
Data.
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Learning Linked Data
• RDF is a language for data – DC, SKOS, LCSH... – the “words” of its dictionaries – RDF Triples based on a “sentence grammar”
• Fluency in RDF – Language designed for humans for processing by
machines – Software tools to read, analyze, compose data... – “RDF as a second language”
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