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Linked Library Data. Modeling Metadata for the [Semantic] Web. Presented 2010-11-19 Columbia University Digital Library Seminar Series Corey A Harper. Topical Overview. Semantic Web Intro Linked Open Data Graphs: Entity – Attribute – Value A Few Examples Library Data. - PowerPoint PPT Presentation
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Linked Library Data
Modeling Metadata for the [Semantic] Web
Presented 2010-11-19Columbia University Digital Library Seminar Series Corey A Harper
2010-11-19 Harper - Linked Library Data - Columbia University 2
Topical Overview
• Semantic Web Intro• Linked Open Data
– Graphs: Entity – Attribute – Value– A Few Examples
• Library Data
2010-11-19 Harper - Linked Library Data - Columbia University 3
Topical Overview (cont)
• Linked Library Data– SKOS and Authority Control– FRBR and Bibliographic Data– National Libraries
• Resource Description and Access (RDA)
• Dublin Core Metadata Initiative
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Semantic Web
• TBL’s original vision– “Weaving the Web” – 1999
• Then: Focus on Machine Reasoning – Scientific American Article
• Now: Focus on things & links– Reasoning becoming lower level
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Semantic Web
• Originally:– Metadata standard built on XML– Metadata about “Web” things
• Eventually:– Metadata about all things– Metadata about relationships
between things
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Semantic Web Terminology
• Resource: Any thing• Class: Abstraction of a type of thing• Individual: An instance of a class• Property: An attribute of an individual• Ontology: A domain specific collection of
classes and properties• Statement/Triple:
– A Resource (subject) - Nodes– A Property (predicate) - Arcs– A Value (object) - Nodes
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Semantic Web Terminology
• Graphs: Representations of statements about resources
• Nodes: The Subjects and Objects in a Graph• Arcs: The Predicates in a Graph• Literals:
“Objects” represented as strings (constant values) rather than things (URI References)
• Domains and Ranges: Constraints on Nodes• For Example…
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2010-11-19 Harper - Linked Library Data - Columbia University 9
RDF
• Resource Description Framework• Formally Begun in 1999• Ideas from 1995• Finalized in 2004• Frighteningly complex at times…
– “Directed Labeled Graphs”
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SemWeb Value Proposition
• Formally Modeled (Meta) Data• Formal Semantics Declaration• Increased Granularity compared to
record-based Metadata• Improved Interoperability
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“The vast bulk of data to be on the Semantic Web is already sitting in databases … all that is needed [is] to write an adapter to convert a particular format into RDF and all the content in that format is available.”
-Tim Berners-Lee in an interview with the Consortium Standards Bulletin
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Linked Open Data
• Use URIs as names for things • Use HTTP URIs so that people can look
up those names. • When someone looks up a URI, provide
useful information. • Include links to other URIs. so that they
can discover more things. http://www.w3.org/DesignIssues/LinkedData.html
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2010-11-19 Harper - Linked Library Data - Columbia University 14
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2010-11-19 Harper - Linked Library Data - Columbia University 16
Linked Data Cloud
• Automated generation– Comprehensive Knowledge Archive N
etwork (CKAN)– Vocabulary of Interlinked Datasets (
voiD)– Basically, catalog your metadata!
• Recent criticism: data quality
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Data in the Cloud• Hubs in the May 2008 Version:
– FOAF– DBPedia
• Myriad Sources coming online:– Thompson Reuters– New York Times– British Broadcasting Corporation– Google and Facebook– More and More Library Data
–Geonames–MusicBrains
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DBpedia
• Structured Wikipedia Data• Genres, Influences, External Links• Multi-lingual / Multi-script labels• Rich Semantics• Many linkages to other datasets
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DBpedia
• 3.4 Million “things” described• Ontology based on “infoboxes”
– 1.5 million things classified
• Approx. 50,000 “Properties”– Approx. 1,200 defined in ontology
• Brief Example
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Domain Modeling
• Starting from application / goal / function
“To guide and evaluate our designs, we need objective criteria that are founded on the purpose of the resulting artifact, rather than based on a priori notions of naturalness or Truth.” – Gruber, 1993
• Does this apply to Libraries? FRBRer?
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DBPedia Model
• Partial basis in data entry conventions• InfoBox’s, and InfoBox Templates• Metadata Entry Format• Partial source of Ontology
– Class Structure– Vocabulary Design
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DBpedia
• 3.4 Million “things” described• Ontology based on “infoboxes”
– 1.5 million things classified– http://wiki.dbpedia.org/Ontology
• Approx. 50,000 “Properties”– Approx. 1,200 defined in ontology
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2010-11-19 Harper - Linked Library Data - Columbia University 26
More Examples
• British Broadcasting Corporation– Programmes, Music, Wildlife
• Google Refine• Data.gov and data.gov.uk• NY Times
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What *things* are in our data???
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…Librarydata is extremelycomplicated
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Bibliographic Data
• Rich stores of MARC, MODS, &c.• Robust Controlled Vocabularies
– Subject Heading lists– Code lists– Thesauri
• Emerging data model in FR*
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Bibliographic Vocabs
• Bibliographic Ontology– Zotero, Omeka, EPrints and Others
• FRBR – unofficial– And now Official (Thank you IFLA!)
• ISBD
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Library Authority Data
“Include links to other URIs. so that they can discover more things.”
Short of providing and linking to URIs, this *is* authority data.
This is what our authority files are for.
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Library Controlled Vocabularies: Benefits
• Reputation - Trusted Tradition• Mature - Time tested and carefully
developed• General & Comprehensive - Cover
large knowledge spaces
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SKOS
• Simple Knowledge Organization System
• Properties and Classes for describing Controlled Vocabulary
RDF Pageskos:primaryTopic
skos:person
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LCSH in Dublin Core
• Encoding Scheme for DC Subject• No easy way to draw on equivelent
terms and cross-references• Abstract Model, RDF and SKOS
could enable applications to make use of the whole vocabulary
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LCSH as a Web Service!
• Uses principles of linked data• lcsh.info -> id.loc.gov• People noticed when taken down• Links to French Subject Headings• URIs for Literal String lookup• http://id.loc.gov/authorities/label/World Wide Web
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2010-11-19 Harper - Linked Library Data - Columbia University 37
Other Vocabularies
• Thesaurus for Economics• French Subject Headings• Swedish Subject Headings• IconClass (not on web yet)• OCLC Terminology Services• Dewey Decimal Classification• Virtual International Authority File
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Linked Library Data
• VIAF, LCSH, MARC Codes• Open Library, XC, Kualli OLE• Library of Congress, OCLC• Hungarian, German, British, Swedish
National Libraries• Formalized Efforts: W3C, IFLA & RDA
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Kungliga Biblioteket
Image co
urte
sy o
f Martin
M
alm
stem
http
://blo
g.lib
ris.kb.se
/sem
web/?
p=
7
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National Széchényi Library
“Our RDFDC, FAOF and SKOS statements are linked together. Our name authority is matched with the DBPedia name files and URI aliases are handled as owl:sameAs statements.” -Adam Horvath
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W3C LLD XG
• “Incubator Group”• Membership:
– Researchers, Consultants, Librarians– National Libraries: Germany, France,
LoC, Sweden– OCLC & IFLA
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2010-11-19 Harper - Linked Library Data - Columbia University 43
W3C LLD XG Goals
• Collecting, Curating and Clustering over 50 Use Cases
• Mining use cases for functional requirements and design patterns
• Recommendations to W3C– Should lead to Working Groups
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RDA Development
• RDA elements, roles and vocabularies have been provisionally registered
• IFLA FRBRer and ISBD elements and vocabularies have been officially registered
• Discussions about long term maintenance of both RDA and the vocabularies
• Effort to create multi-language RDA Vocabularies
RD
A S
lides A
dapte
d fro
m D
iane
Hillm
ann
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RDA Elements Listing
334!
2010-11-19 Harper - Linked Library Data - Columbia University 46
RDA Elements Listing
334!
Base material
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Detail: Base Material
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Detail: Base Material
URI
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RDA Base Material Vocabulary
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RDA WEMI Relationships
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Detail: RDA WEMI Relationship
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Metadata Registries
• Formerly NSDL Registry– Now “Open Metadata Registry”– Managing Vocabularies– Providing Vocabulary Services
• DCMI Registry Community• DCMI Architecture Forum
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DCMI and the Semantic Web
• Collaboration from the start• Libraries (esp. OCLC) were at the
table• Perception of DCMI as DCMES
– DCMI = Metedata Vocab / Framework– DCMES = Metadata Record Format
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DCMI and the Semantic Web
• Every example above had dcterms• DCMI as Research Institute and
Metadata Think Tank– Modeling Work– Metadata Registries– Application Profiles– Description Set Profiles– Singapore Framework
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Changing Role of DCMI
• Mike Bergman at DC2010:– Reference Metadata– Reference Concepts– Mapping Predicates
• “Mappings should be approximate”
– Usage Guidelines• Compliment to W3C Standards
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Why Does This Matter?Our descriptions no longer stand alone!Connect our data with the rest of the WEBAllow others to reuse more easily
– FOAF– DBPedia– Geonames– MusicBrains– New York Times– Thompson Reuters– Government Data - data.gov– British Broadcasting Corporation
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Conclusions
• Distributed bibliographic control environment– Linking Data– Focus on identification over description
• “In short, by treating values as non-literal resources and assigning URIs to them we give ourselves (and others) the hooks on which to hang further descriptions.” - Andy Powell
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Endless possibilities
• This barely scratches the surface• The Giant Global Graph!!• With more soundly modeled
bibliographic and authority data…– Terminology Services– Context sensitive
interfaces– Customized Exhibits
– Mashups– Web Services– User Profiling– Collaboration tools
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Continuing Challenges
• Emerging Technology• Design Patterns• Complexity (http-range14)• Existing Technical Infrastructure• Bootstrapping• Business Cases
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More Information
• W3C LLD XG:http://www.w3.org/2005/Incubator/lld/wiki/Main_Page
• ALA LLD Interest Group:– http://kcoyle.net/lld-ala.html
• IFLA Semantic Web SIG– https://wiki.d-nb.de/x/vA10Ag
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Thanks!
Questions?