Transcript Linked Library Data Modeling Metadata for the [Semantic] Web Presented 2010-11-19 Columbia University Digital Library Seminar Series Corey A Harper.

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
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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
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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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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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Linked Data Cloud
• Automated generation
– Comprehensive Knowledge Archive
Network (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
–Geonames
–MusicBrains
• Myriad Sources coming online:
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Thompson Reuters
New York Times
British Broadcasting Corporation
Google and Facebook
More and More Library Data
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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
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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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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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…Library
data is
extremely
complicated
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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
skos:primaryTopic
RDF Page
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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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Other Vocabularies
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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
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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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Image courtesy of Martin Malmstem
http://blog.libris.kb.se/semweb/?p=7
Kungliga Biblioteket
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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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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 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
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RDA Slides Adapted from Diane Hillmann
RDA Development
RDA Elements Listing
334!
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RDA Elements Listing
Base material
334!
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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
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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 WEB
Allow others to reuse more easily
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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 nonliteral 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…
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Mashups
Web Services
User Profiling
Collaboration tools
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– Terminology Services
– Context sensitive
interfaces
– Customized Exhibits
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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!
[email protected]
212.998.2479
Questions?
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