M.L.Zeng @ ISSAI, Helsinki,2007 4

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Introductory Review ofCurrentKnowledge OrganizationSystems/Structures/Services(KOS)

Marcia Lei ZengSecond International Seminar on SubjectAccess to Information, Helsinki,Finland, 29-30 November 2007

M.L.Zeng @ ISSAI, Helsinki,2007 2

Purpose of this talk

• Introduce different types ofknowledge organizationsystems/structures/services(KOS)

• Provide a commonterminology and background


1. KOS overview (1)

Knowledge organizationsystems/structures/services(KOS) encompass all types ofschemes for organizinginformation and promotingknowledge management.– (Gail Hodge, 2000)


1. KOS overview (2)

These systems• model the underlying semantic

structure of a domain, and• provide semantics, navigation, and

translation through labels,definitions, typing, relationships,and properties for concepts.– (Hill et al. 2002, Koch and Tudhope 2004).

A Taxonomy of KOS

Term Lists:Authority Files

Synonym Rings

Classification &Categorization:

Subject Headings

Classification schemesTaxonomies

Categorization schemes

Relationship Models: OntologiesSemantic networks

Thesauri

Glossaries/DictionariesPick lists

GazetteersDirectories

Metadata-likeModels:

Function

Structure


2. Fundamentals of KOS Approaches

• 2.1 Eliminating ambiguity• 2.2 Controlling synonyms or

equivalents• 2.3 Making explicit semantic

relationships– Hierarchical relationships– Hierarchical + other associate

relationships• 2.4 Presenting relationships as well

as properties of concepts

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2.1 Eliminating ambiguity

• Ambiguity: terms having thesame spelling (homographs)that represent differentconcepts or meanings

• Ambiguity exists when a giventerm can be used to representcompletely different concepts.

Ambiguity / Homographs

Source: Z39.19-2005, p.25


To eliminate ambiguity (1)

1. Adding a qualifier to a term-- one of the major methods used

by almost every type of KOS,especially lists of subjectheadings and thesauri.

• e.g., Mercury (automobile)


2. Providing a scope note-- another major method used by

almost every type of KOS,especially lists of subjectheadings, classifications, andthesauri.


Screenshot from MeSHhttp://www.nlm.nih.gov/mesh/MBrowser.htmlEntry: mercury


http://www.nlm.nih.gov/mesh/MBrowser.html



3. providing a context of a term



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What are these?

• Flying Horse• King Fisher• Royal Challenge• Heineken• Budweiser• Miller-Lite• Bud-Light

Drinks• Flying Horse• King Fisher• Royal Challenge• Taj Mahal• Hayward’s 2000• Heineken• Corona• Budweiser• Miller-Lite• Bud-Light

Lists (Picklists)A type of controlled vocabulary induced in

NISO Z39.19 Standard


• Lists are used to describe aspects of contentobjects or entities that have a limited number ofpossibilities.

• Examples include:– geography (e.g., country, state, city),– language (e.g., English, French, Swedish),– format (e.g., text, image, sound), or– … …


Lists can be used effectively forboth browsing and searching.

• In browsing, items are directlyaccessed when the list of termsis reviewed and one term isselected


Source: http://www.ncbi.nlm.nih.gov/genome/guide/human/resources.shtml

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• In searching, a list may beused to access content in asingle term search, or the termsfrom the list may be used tolimit a retrieved set by anotherattribute of interest for the user(one or more terms in thesearch).


Source: Google’s advanced search http://www.google.com

pick lists

Waterford County Image Archivehttp://www.waterfordcountyimages.org


Waterford County Image Archivehttp://www.waterfordcountyimages.org


List - Definition, Purpose, and Uses• A list (also called a pick list) is

a limited set of terms arrangedas a simple alphabetical list orin some other logically evidentway.– A list is a series of terms in some

sequential order.– Terms can be ordered

alphabetically, chronologically,numerically, etc.

Exercise: Which list isbetter?

http://www.google.com

http://www.waterfordcountyimages.org

http://www.waterfordcountyimages.org

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• The defining characteristics ofa list are that the terms:· are all members of the same set

or class of items (e.g., countries,products)

· are not overlapping in meaning· are equal in terms of specificity

(granularity)


Typical applications

• Lists are frequently used todisplay small sets of terms thatare to be used for quitenarrowly defined purposessuch as a web pull-down list orlist of menu choices.


2. Fundamentals of KOS Approaches

• 2.1 Eliminating ambiguity• 2.2 Controlling synonyms or


relationships– Hierarchical relationships– hierarchical + other associate

relationships• 2.4 Presenting relationships as

well as properties of concepts


2.2 Controlling synonyms orequivalents• Synonyms: terms with the same or

similar meanings1. True synonyms (unusual)

– mean exactly the same thing and areused in precisely the same context

2. Near synonyms (most common)


1. True Synonyms• common and technical names

– salt vs. sodium chloride• changes in usage of terms over time

– electronic calculating machines vs.computers

• in different languages– eyeglasses, spectacles, glasses

• acronyms– BBC, British Broadcasting Company;

MPG, miles per gallon• variant spellings:

– cancelled, canceled; honor, honour


2. Near Synonyms

• Same stem– computing, computers,

computed,microcomputers,supercomputers

• Overlapping concepts– medicine, drugs– fired, laid off– forest, woods– arid, dry

• General andspecific termsCoffee– Double Espresso– Latte– Cappuccino– Short Black– Macchiato– Flat White– etc.

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Synonymy

Source: Z39.19-2005, p.25M.L.Zeng @ ISSAI, Helsinki,2007 32

• Each distinct concept shouldrefer to a unique linguisticform.

• Information or content that isprovided to a user should notspread across the system undermultiple access points, butshould be gathered together inone place.

… …150 World War, 1939-1945450 European War, 1939-1945450 Second World War, 1939-

1945450 World War 2, 1939-1945450 World War II, 1939-1945450 World War Two, 1939-1945

Source: FAST: FacetedApplication of SubjectTerminologyhttp://fast.oclc.org/

Controlling synonyms: there will only be one term used to representa given concept or entity.

or:

World War, 1939-1945UF European War, 1939-1945UF Second World War, 1939-1945UF World War 2, 1939-1945UF World War II, 1939-1945UF World War Two, 1939-1945

European War, 1939-1945USE World War, 1939-1945

Second World War, 1939-1945USE World War, 1939-1945

World War 2, 1939-1945USE World War, 1939-1945

World War II, 1939-1945USE World War, 1939-1945

World War Two, 1939-1945USE World War, 1939-1945

AuthorityFile

Thesaurus


Source: Art and ArchitectureThesaurus (AAT)


Source: Medical Subject Headings (MeSH)

Synonym RingsA type of controlled vocabulary induced in

NISO Z39.19 Standard

http://fast.oclc.org/

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astronaut

spaceman cosmonaut

spationaut taikonaut

A synonym ring connects a set of words that aredefined as equivalent for retrieval.

An example from International SEMATECH.

A search for Silicon would look like this:

Your search was submitted as “CILICON” or “SI”


Synonym Rings are used--• to expand queries for content objects

– If a user enters any one of these terms asa query to the system, all items areretrieved that contain any of the termsin the cluster.

• in systems where the underlyingcontent objects are left in theirunstructured natural languageformat– The control is achieved through the

interface by drawing together similarterms to these clusters.

• in conjunction with search engines

Poverty mitigation

Poverty alleviation

Poverty elimination

Poverty reducation

Poverty eradication

Poverty abatement

Poverty prevention

Poverty reduction

Rings can include all kinds ofsynonyms - true,misspellings, predecessors,abbreviationsSource: Bedford, 2006 ppt.


Exercise

• Find synonyms of this type ofobject:


2. Fundamentals of KOS Approaches• 2.1 Eliminating ambiguity• 2.2 Controlling synonyms or



relationships• 2.4 Presenting relationships as well

as properties of concepts

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2.3 Making explicit semantic relationships –Hierarchical relationships

BirdsCardinalsDovesRobinsWrens

All specific names ofbirds are kinds of birds.

Phylum: ChordataClass: Reptilia

Subclass: AnapsidaOrder: Testudines

Suborder: CryptodiraFamily: Dermochelyidae

Genus: DermochelysSpecies: Dermochelys coriacea

(Leatherback turtle)

Scientific TaxonomyAn example: Leatherback turtle


superordinate classes (e.g., parents). coordinate classes (e.g., siblings)

. . subordinate classes (e.g., children). . subordinate classes

. coordinate classes

. coordinate classes. . subordinate classes

relationship types: generic, instance, and whole-part

Classifications



Part / WholeCause / EffectProcess / AgentAction / ProductAction / PatientConcept or Thing / PropertiesConcept or Thing / OriginsThing or Action / Counter-agentRaw material / ProductAction / Property

Antonyms

Bicycle / Bicycle WheelAccident / InjuryVelocity measurement / SpeedometerWriting / PublicationTeaching / StudentSteel alloy / Corrosion resistanceWater / WellPest / PesticideGrapes / WineCommunication / Communication

skillsSingle people / Married people

Relationship Example

2.3 Making explicit semantic relationships –Associative relationships (not hierarchical)

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M.L.Zeng @ ISSAI, Helsinki,2007 49 M.L.Zeng @ ISSAI, Helsinki,2007 50

Source: Z39.19-2005, p.29

KOS in Use at World Bank

• Topic Thesaurus (500,000+English terms, French andSpanish language versions inprogress now)

• Topic Classification Scheme(30 top classes, 700+ subtopics,300+ subsubtopics)

• Business Function Thesaurus(50,000 terms and growing)

• Business FunctionClassification Scheme (5business areas, 30 lines ofbusiness, 300+ businessprocesses)

• Country-Region classificationscheme (6 regions, ca. 200countries)

• Content Type ClassificationScheme (8 content types, 300+secondary content types – inrefinement now)

• Media-Format ClassificationScheme

• Country Name Authority Control(synonym, predecessor, successorsources)

• Edition Statements AuthorityControl

• Publisher Name AuthorityControl

• Organization Authority Control• Language Authority Control• Series Name/Collection Title

Authority Control• Translation Type Authority

Control

Source: Bedford, 2007, ASIST


Pick lists Hierarchicaltaxonomy

SynonymRings

SynonymRings

Vision of An Enterprise Advanced Search

Source: Revised based on Bedford, 2006 ppt.


Synonym Rings

Thesaurus

Metadata

Source: Revised based on Bedford, 2006 ppt.

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2. Fundamentals of KOS Approaches• 2.1 Eliminating ambiguity• 2.2 Controlling synonyms or



relationships

• 2.4 Presentingrelationships as well asproperties of concepts M.L.Zeng @ ISSAI, Helsinki,2007 56

2.4 Presenting relationships aswell as properties of concepts

• Entity types• Relationship types• Properties


Semantic networks

organize sets of termsrepresenting concepts,modeled as the nodes in anetwork of variablerelationship types.


UMLS Semantic Network

135 Semantic Types (link) and 54 Semantic Relation Types (link)

Source: Noy, N. F. and Tu, S.W. (2003).

Ontologies

Classes

attributes

instances

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M.L.Zeng @ ISSAI, Helsinki,2007 61 M.L.Zeng @ ISSAI, Helsinki,2007 62


The Graph view of relations


A Taxonomy of KOS © 2007 Zeng

OntologiesSemantic networks

Thesauri

Glossaries/DictionariesPick lists

xxxxxpresenting properties

xxxxxxxxxestablishingrelationships: associative

xxxxxxx xxxxestablishingrelationships: hierarchical

xxxxxxxxx xxxxxxcontrolling synonymsxxxxxxxxx xxxxxeliminating ambiguity

establishing

xestablishingxxxx

function

Two-dimensions

Term Lists: Synonym RingsFlat

structure

Classification &Categorization:

Subject Headings

Classification schemesTaxonomies

Categorization schemes

Relationship Models:

GazetteersDirectories

Authority Files

Metadata -likeModels:

Multipledimensions

Majo

r fun

ction

s


Networked KOSè NKOS

• KOS are not used in isolation;• KOS may be used, re-used, and re-

purposed in web-based services;• KOS are used for:

– organizing, indexing, cataloging, and searching,AND

– learning, knowledge modeling, reasoning, etc.• NKOS need to be machine-processable,

machine-understandable– (more to discuss later today)

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References

• Hodge, Gail (2000). Systems of Knowledge Organization forDigital Libraries: Beyond Traditional Authority Files. Washington,DC: Council on Library and Information Resources.http://www.clir.org/pubs/reports/pub91/contents.htmlhttp://www.clir.org/pubs/reports/pub91/pub91.pdf

• Hill, Linda, Buchel, Olha, Janee, Greg, and Zeng, Marcia L.2002. Integration of knowledge organization systems intodigital library architectures: In: Mai, Jens-Erik, et al. ed.:Advances of classification research, volume 13, proceedings of the13th ASIST SIG/CR Workshop, 17 November 2002Philadelphia PA, pp. 62-68.

• Koch, Traugott and Tudhope, Douglas. 2004. User-centredapproaches to Networked Knowledge OrganizationSystems/Services (NKOS): Background.http://www2.db.dk/nkos-workshop/#Background

http://www.clir.org/pubs/reports/pub91/contents.html

http://www.clir.org/pubs/reports/pub91/pub91.pdf

http://www2.db.dk/nkos-workshop/#Background

M.L.Zeng @ ISSAI, Helsinki,2007 4

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