Developing a Metadata Infrastructure for Information Access: What, Where, When and Who?

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Developing a Metadata Infrastructure for
Information AccessWhat, Where, When and Who?
Prof. Ray R. Larson University of California,
BerkeleySchool of Information
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Overview

• Metadata as Infrastructure
• What, Where, When and Who?
• What are Entry Vocabulary Indexes?
• Notion of an EVI
• How are EVIs Built
• Time Period Directories
• Mining Metadata for new metadata
• 4W Demo
• New Project Bringing Lives to Light

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Metadata as Infrastructure

• The difference between memorization and
  understanding lies in knowing the context and
  relationships of whatever is of interest. When
  setting out to learn about a new topic, a
  well-tested practice is to follow the traditional
  5Ws and the H Who?, What?, When?, Where?,
  Why?, and How?

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Metadata as Infrastructure

• The reference collections of paper-based
  libraries provide a structured environment for
  resources, with encyclopedias and subject
  catalogs, gazetteers, chronologies, and
  biographical dictionaries, offering direct
  support for at least What, Where, When, and Who.
• The digital environment does not yet provide an
  effective, and easily exploited, infrastructure
  comparable to the traditional reference library.

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What?

• Searching texts by topic, e.g. Dewey, LCSH, any
  subject index, or category scheme applied to
  documents.
• Two kinds of mapping in every search
• Documents are assigned to topic categories, e.g.
  Dewey
• Queries have to map to topic categories, e.g.
  Deweys Relativ Index from ordinary words/phrases
  to Decimal Classification numbers.
• Also mapping between topic systems, e.g. US
  Patent classification and International Patent
  Classification.

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What searches involve mapping to controlled
vocabularies
Thesaurus/ Ontology
Texts
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Building a Search Term Recommender
Start with a collection of documents.
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Classify and index with controlled vocabulary Or
use a pre-indexed collection.
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ProblemControlled Vocabularies can be difficult
for people to use.
pass mtr veh spark ign eng
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SolutionEntry Level Vocabulary Indexes.
Index
EVI
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What and Entry Vocabulary Indexes

• EVIs are a means of mapping from users
  vocabulary to the controlled vocabulary of a
  collection of documents

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Building and Searching EVIs
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Technical Details
For noun phrases
Internet DB indexed with a controlled vocabulary.
Building an Entry Vocabulary Module (EVI)
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Association Measure
C C t a
b t c d
Where t is the occurrence of a term and C is the
occurrence of a class in the training set
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Association Measure

• Maximum Likelihood ratio

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Alternatively

• Because the evidence terms in EVIs can be
  considered a document, you can also use IR
  techniques and use the top-ranked classes for
  classification or query expansion

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EVI example
Index termpass mtr veh spark ign eng
EVI 1
User Query Automobile
Index termautomobiles OR internal
combustible engines
EVI 2
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But why stop there?
Index
EVI
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Which EVI do I use?
Index
EVI
Index
EVI
Index
EVI
Index
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EVI to EVIs
Index
EVI
EVI2
Index
EVI
Index
EVI
Index
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Why not treat language the same way?
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Support for the Learner with a Query
Facet Vocabulary Displays WHAT
Thesaurus Cross- e.g. LCSH
references WHERE Gazetteer Map WHEN
Period directory Timeline WHO Biograph.
dict. Personal e.g. Whos Who relations
Any catalog Archives, Libraries, Museums, TV,
Publishers
Any resource Audio, Images, Texts, Numeric data,
Objects, Virtual reality, Webpages
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It is also difficult to move between different
media forms
Thesaurus/ Ontology
Texts
EVI
Numeric datasets
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Searching across data types

• Different media can be linked indirectly via
  metadata, but often (e.g. for socio-economic
  numeric data series) you also need to specify
  WHERE to get correct results

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But texts associated with numeric data can be
mapped as well
Thesaurus/ Ontology
Texts
EVI
EVI
captions
Numeric datasets
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But there are also geographic dependencies
Thesaurus/ Ontology
Texts
EVI
EVI
captions
Maps/ Geo Data
Numeric datasets
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WHERE Place names are problematic

• Variant forms St. Petersburg, ????? ?????????,
  Saint-Pétersbourg, . . .
• Multiple names Cluj, in Romania / Roumania /
  Rumania, is also called Klausenburg and
  Kolozsvar.
• Names changes Bombay ? Mumbai.
• HomographsVienna, VA, and Vienna, Austria
• 50 Springfields.
• Anachronisms No Germany before 1870
• Vague, e.g. Midwest, Silicon Valley
• Unstable boundaries 19th century Poland
  Balkans USSR
• Use a gazetteer!

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WHERE. Geo-temporal search interface. Place
names found in documents. Gazetteer provided lat.
long. Places displayed on map.
Timebar?
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Zoom on map. Click on place for a list of
records. Click on record to display text.
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So geographic search becomes part of the
infrastructure
Thesaurus/ Ontology
Texts
EVI
Gazetteers
captions
Maps/ Geo Data
Numeric datasets
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WHEN Search by time is also weakly supported

• Calendars are the standard for time
• But people use the names of events to refer to
  time periods
• Named time periods resemble place names in being
• Unstable European War, Great War, First World
  War
• Multiple Second World War, Great Patriotic War
• Ambiguous Civil war in different centuries in
  England, USA, Spain, etc.
• Places have temporal aspects periods have
  geographical aspects When the Stone Age was,
  varies by region

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Vocabularies are the key! Want Kung-fu
movies? Use LCSH Hand-to-hand fighting,
oriental, in motion pictures.
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Time period directories link via the place (or
time)
Thesaurus/ Ontology
Texts
EVI
Gazetteers
captions
Maps/ Geo Data
Numeric datasets
Time Period Directory
Time lines, Chronologies
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WHEN Time Period Directory Timeline
Link to Catalog Link to Wikipedia
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WHO Biographical Dictionary Complex
relationships
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Any document, object, or performance
Connect it with its context and other resources.
Facet Vocabulary Displays WHAT
Thesaurus Cross- e.g. LCSH
references WHERE Gazetteer Map WHEN
Period directory Timeline WHO Biograph.
dict. Personal e.g. Whos Who relations
Any catalog Archives, Libraries, Museums, TV,
Publishers
Any resource Audio, Images, Texts, Numeric data,
Objects, Virtual reality, Webpages
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Demo of search interface
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Related places
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Potentially related people
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Potentially related periods
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Find out more about this area.
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Different Browsing Options!
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More information about the country of India
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ECAI Cultural Atlases presenting history in its
geographical chronological contexts
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Mongol Empire Video
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Demo Interface

• http//ecai.berkeley.edu/imls2004/imls4w/

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New Project Bringing Lives to Light
Biography in Context
Ray R. Larson, Michael Buckland, Fredric
Gey University of California, Berkeley
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Overview

• Focussing on the Who in Who, What, Where and When
• Types of Biographical Markup

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WHEN, WHERE and WHO

• Catalog records found from a time period search
  commonly include names of persons important at
  that time. Their names can be forwarded to, e.g.,
  biographies in the Wikipedia encyclopedia.

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Place and time are broadly important across
numerous tools and genres including, e.g.
Language atlases, Library catalogs, Biographical
dictionaries, Bibliographies, Archival finding
aids, Museum records, etc., etc. Biographical
dictionaries are also heavy on place and time
Emanuel Goldberg, Born Moscow 1881. PhD under
Wilhelm Ostwald, Univ. of Leipzig, 1906.
Director, Zeiss Ikon, Dresden, 1926-33. Moved to
Palestine 1937. Died Tel Aviv, 1970. Life as a
series of episodes involving Activity (WHAT),
WHERE, WHEN, and WHO else.
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A new form of biographical dictionary would link
to all
Biographical Dictionary
Thesaurus/ Ontology
Texts
EVI
Gazetteers
captions
Maps/ Geo Data
Numeric datasets
Time Period Directory
Time lines, Chronologies
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Projected Work

• Develop XML markup for Biographical Events
• Most likely to be adaptation and extension of
  existing biographical event markup
• Example EAC/EAD
• Harvest biographical resources
• Wikipedia, etc.
• Integrate as next generation of current interface

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EAC/EAD
ltbioghistgt ltheadgtBiographical
Notelt/headgt ltchronlistgt
ltchronitemgt ltdategt1892, May
7lt/dategt lteventgtBorn,
ltgeognamegtGlencoe, Ill.lt/geognamegtlt/eventgt
lt/chronitemgt ltchronitemgt
ltdategt1915lt/dategt
lteventgtA.B., ltcorpnamegtYale University,
lt/corpnamegtNew Haven, Conn.lt/eventgt
lt/chronitemgt ltchronitemgt
ltdategt1916lt/dategt
lteventgtMarried ltpersnamegtAda Hitchcocklt/persnamegt
lt/eventgt
lt/chronitemgt ltchronitemgt
ltdategt1917-1919lt/dategt
lteventgtServed in ltcorpnamegtUnited States
Armylt/corpnamegtlt/eventgt lt/chronitemgt
lt/chronlistgt lt/bioghistgt
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Wikipedia data
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A Metadata Infrastructure
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Acknowledgements

• Electronic Cultural Atlas Initiative project
• This work is being supported supported by the
  Institute of Museum and Library Services through
  a National Leadership Grant for Libraries
• Contact ray_at_ischool.berkeley.edu