Cornell CS 502 Metadata for the Web From Discovery to Description CS 502 – 20020224 Carl Lagoze – Cornell University
Jan 23, 2016
Cornell CS 502
Metadata for the WebFrom Discovery to Description
CS 502 – 20020224Carl Lagoze – Cornell University
Cornell CS 502
The fifteen Dublin Core Elements
Creator Title Subject
Contributor Date Description
Publisher Type Format
Coverage Rights Relation
Source Language I dentifi er
http://dublincore.org/usage/terms/dc/current-elements/http://dublincore.org
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A Pidgin for Digital Tourists
• Metadata is language• Dublin Core is a small and simple language -- a
pidgin -- for finding resources across domains.• Speakers of different languages naturally
"pidginize" to communicate– E.g., tourists using simple phrases to order beer
("zwei Bier bitte" "dva pivo" "biru o san bai"...)
• We are all "tourists" on the global Internet.
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What is the Dublin Core (1)
• A simple set of properties to support resource discovery on the web (fuzzy search buckets)?
DomainIndependent
view
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What is Dublin Core (2)?
• An extensible ontology for resource desciption?
Gre
ate
r Fun
ction
ality
&
Cost
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What is the Dublin Core (3)?
• A cross-domain switchboard for interoperable metadata?
Switchboard
DublinCore
MARC
INDECSIMS
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Dublin Core Qualifiers
• From fuzzy buckets to more specific description
• Model of “graceful degradation”– Support both simplicity and specificity– Intra-domain and inter-domain semantics
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Varieties of qualifiers: Element Refinements
• Make the meaning of an element narrower or more specific.
• Narrowing implies an is a relationship – a "date created“ is a "date“– an "is part of relation“ is a "relation“
• If your software does not understand the qualifier, you can safely ignore it.
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Varieties of Qualifiers: Value Encoding Schemes
• Says that the value is– a term from a controlled vocabulary (e.g., Library of
Congress Subject Headings)– a string formatted in a standard way (e.g., "2001-05-
02" means May 3, not February 5)
• Even if a scheme is not known by software, the value should be "appropriate" and usable for resource discovery.
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A Grammar of Dublin Core
• http://www.dlib.org/dlib/october00/baker/10baker.html
• By design not as subtle as mother tongues, but easy to learn and extremely useful in practice
• Pidgins: small vocabularies (Dublin Core: fifteen special nouns and lots of optional adjectives)
• Simple grammars: sentences (statements) follow a simple fixed pattern...
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Example Dublin Core statements
• Resource has Title 'Grammar of Dublin Core'.• Resource has Creator 'Tom Baker'.• Resource has Subject 'Metadata'.• Resource has Relation http://foo.org/file.htm.
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Resource has property
DC:CreatorDC:TitleDC:SubjectDC:Date...
X
implied subject
impliedverb
one of 15properties
property value(an appropriateliteral)
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Resource has property
DC:CreatorDC:TitleDC:SubjectDC:Date...
X
implied subject
impliedverb
one of 15properties
property value(an appropriateliteral)
[optional qualifier]
[optional qualifier]
qualifiers(adjectives)
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Resource has Date "2000-06-13"Revised
ISO8601
Resource has Subject "Languages -- Grammar"LCSH
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Dumb-Down Principle for Qualifiers
• The fifteen elements should be usable and understandable with or without the qualifiers
• Qualifiers refine meaning (but may be harder to understand)
• Nouns can stand on their own without adjectives
• If your software encounters an unfamiliar qualifier, look it up -- or just ignore it!
• "has a“ relations break the model– E.g., a creator has a hair color
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Resource has Date "2000-06-13"Revised
ISO8601
Resource has Subject "Languages -- Grammar"LCSH
Test for “good““ qualifiers:cover and ask: -- Does the statement still make sense? -- Is it still correct?
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Resource has subjectaudience
Resource has creatoraffiliation
“Incorrect” Qualification
“Cornell University”
“pre-schoolers”
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Open questions in this model
• Are uncontrolled and unconstrained values really useful for discovery?
• Is it possible for an organization (DCMI) to control the evolution of a language?
• How can "simple discovery metadata" be combined with complex descriptions? Is there a notion of graceful degradation?
• Can DC serve as a lingua franca (mapping template) among more complex models
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Models for Deploying Metadata
• Embedded in the resource– low deployment threshold– Limited flexibility, limited model
• Linked to from resource– Using xlink– Is there only one source of metadata?
• Independent resource referencing resource– Model of accessing the object through its surrogate– Resource doesn’t ‘have’ metadata, metadata is just
one resource annotating another
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Syntax Alternatives:HTML
• Advantages:– Simple Mechanism – META tags embedded in content– Widely deployed tools and knowledge
• Disadvantages– Limited structural richness (won’t support
hierarchical,tree-structured data or entity distinctions).
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Dublin Core in HTML
• http://www.dublincore.org/documents/2000/08/15/dcq-html/
• HTML constructs– <link> to establish pseudo-namespace– <meta> for metadata statements
• name attribute for DC element (DC.element.ER)
• content attribute for element value
• scheme attribute for encoding scheme or controlled vocabulary
• lang attribute for language of element value
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Dublin Core in HTML example
<link rel="schema.DC" href="http://purl.org/dc/elements/1.1"> <meta name="DC.Title" content="Business Unusual”><meta name=“DC.Title” lang=“es” content=“negocio inusual”> <meta name="DC.Creator" content="Carl Lagoze"> <meta name="DC.Subject" content="bibliographic control web cataloging "> <meta name="DC.Date.Created" scheme="W3CDTF"
content="2000-10-23"> <meta name="DC.Format" content="text/html"> <meta name="DC.Identifier" content="http://lcweb.loc.gov/lagoze_paper.html">
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Unqualified Dublin Core in XML
http://dublincore.org/documents/2002/09/09/dc-xml-guidelines/
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Multi-entity nature of object description
Photographer
Camera type Software
Computer artist
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Attribute/Value approaches to metadata…
Hamlet has a creator Shakespeare
subject implied verb metadata noun literal
Play
wrig
ht
metadata adjective
The playwright of Hamlet was Shakespeare
R1
“Shakespeare”
“Hamlet”
dc:creator.playwright
dc:title
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…run into problems for richer descriptions…
Hamlet has a creator Stratford
birt
hpla
ce
The playwright of Hamlet was Shakespeare,who was born in Stratford
“Stratford”R1
“Shakespeare”dc:creator.playwright
dc:creator.birthplace
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…because of their failure to model entity distinctions
R1
“Stratford”
creatorR2
name “Shakespeare”
birthplacetitle
“Hamlet”
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Applying a Model-Centric Approach
• Formally define common entities and relationships underlying multiple metadata vocabularies
• Describe them (and their inter-relationships) in a simple logical model
• Provide the framework for extending these common semantics to domain and application-specific metadata vocabularies.
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Events are key to understanding resource complexity?
• Events are implicit in most metadata formats (e.g., ‘date published’, ‘translator’)
• Modeling implied events as first-class objects provides attachment points for common entities – e.g., agents, contexts (times & places), roles.
• Clarifying attachment points facilitates understanding and querying “who was responsible for what when”.
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ABC/Harmony Event-aware metadata ontology• Recognizing inherent lifecycle aspects of
description (esp. of digital content)• Modeling incorporates time (events and
situations) as first-class objects– Supplies clear attachment points for agents, roles,
existential properties
• Resource description as a “story-telling” activity
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Resource-centric Metadata
Title Anna Karenina
Author Leo Tolstoy
Illustrator Orest Vereisky
Translator Margaret Wettlin
Date Created 1877
Date Translated 1978
Description Adultery & Depression
Birthplace Moscow
Birthdate 1828
?
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“translator”
“Margaret Wettlin”“Orest Vereisky”
“illustrator”
“Anna Karenina”
“Tragic adultery andthe search for meaningfullove”
“English”
“author”
“creation”
“1877”“1978”
“translation”
“Russian”
“Leo Tolstoy”"Moscow"
“1828”
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Breaking the metadata bottleneck Human vs. machine generation
• Simple text scraping – HTML tags as hint– Other structural methods
• Natural language methods and machine learning
• Contextual methods– Google (text and image search)
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Putting metadata in its place
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Query engine architecture space
Queries
Structured Unstructured
Data
Structured
Unstructured
1
3
2
4
(Relational)DatabaseSystems
InformationRetrievalSystems