Semantic Mapping through a concept hub Dagobert Soergel College of Information Studies, University of Maryland Department of Library and Information Studies,

Semantic Mappingthrough a concept hub

Dagobert Soergel

College of Information Studies, University of Maryland

Department of Library and Information Studies, University at Buffalo

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Hub

Water transport

Inland water transport

Ocean transport

Traffic station Water transport⊓

Traffic station Inland water tr.⊓

Traffic station Ocean transport⊓

Dewey

387 Water, air, space transportation

386 Inland waterway & ferry transportation

387.5 Ocean transportation

386.8 Inland waterway tr. > Ports

387.1 Ports

LCSH

Shipping


Merchant marine

Harbors

GermanHafen

Mapping through a Hub

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Outline

• Objective: Interoperability Plus

• KOS concept hub

• Method: Knowledge-based, computer-assisted of canonical representations of concepts

• Resulting knowledge base and applications

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Objective

Improve semantic-based search of digital content across multiple collections in multiple languages.

• Interoperability between any two participating KOS(Knowledge Organization Systems)

• Support for search, esp. facet-based search • for any collection indexed by a participating KOS• for free-text search

• Assistance in cataloging (metadata creation) by catalogers or users (social tagging)

• Long-range goal: Web service where a KOS can be uploaded and mappings to specified target KOS are returned

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KOS Concept Hub

• The backbone of the proposed system is a faceted core classification of atomic concepts together with a set of relationships

• Interoperability is achieved by expressing concepts from all participating KOS as a canonical representation:description logic formula using atomic concepts and relationships

• Mapping from KOS to KOS is achieved by reasoning over these canonical representations

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Hub

Water transport


Ocean transport




Dewey





387.1 Ports

LCSH

Shipping


Merchant marine

Harbors

GermanHafen


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Method: How to get DL formulasKey: Efficient creation of canonical representations (DL formulas)

• Apply existing knowledge:Large knowledge base ▬► less effort for processing a new KOS

• Use knowledge of KOS structure for hierarchical inheritance

• Use linguistic analysis of terms and captions

• Eliminate redundant atomic concepts

• Check or produce mapping results from assignment of concepts to the same records

• Get human editors’ input and verification where needed through a user-friendly interface

• KOS “owners” may verify and edit data pertaining to their KOS

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Knowledge base

Requires an ever larger classification and lexical knowledge base containing many kinds of data:

1. A faceted classification of atomic conceptsSeeded from sources with well-developed facets such as the AOD Thesaurus, the Harvard Business Thesaurus, the Art and Architecture Thesaurus, various ontologies

2. Linguistic knowledge bases such as Wordnet and mono-,bi-, and multi-langual dictionaries and thesauri

3. Many KOS (Knowledge Organization Systems), such as LCC, DDC, DMOZ directory, LCSH, Gene Ontology, Schlagwortnormdatei

4. These will over time be fused into one large multilingual knowledge base with many terminological and translation relationships and relationships linking terms to concepts, with an increasing number of concepts semantically represented by a DL formula.

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Examples of derivingDL formulas

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L00 Transportation and trafficL10 Traffic system components

L13 Traffic facilities

L15 Traffic stations

L17 Vehicles

L30 Modes of transportation

L33 Air transport

L37 Water transport

P00 Buildings, constructionP23 Buildings

P27 Architecture

P43 Construction

R00 EngineeringR30 Acoustics

R37 Soundproofing

T70 Military vs. civilian T73 Military

T77 Civilian

Underlying faceted classification

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HE Transportation

HE550-560 Ports, harbors, docks, wharves, etc.

L00 Transportation and traffic T77 Civilian⊓

Inherited: L00 Transportation and traffic T77 Civilian⊓

Added by editor:L15 Traffic stations L37 Water transport⊓

Resolved to:L15 Traffic stations L37 Water transport ⊓ ⊓T77 Civilian

Method: Assigning atomic concepts 1

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NA6300-6307 Airport buildings From database already established:

Airport = L15 Traffic stations L33 Air transport ⊓

Buildings = P23 Buildings

Added by editor T77 Civilian

Resolved to

L15 Traffic stations L33 Air transport ⊓ ⊓

P23 Buildings T77 Civilian⊓


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TL681.S6 Airplanes. Soundproofing From database already established:

Airplane = L17 Vehicles L33 Air transport ⊓

Soundproofing = R37 Soundproofing

Added by editor: Nothing

Resolved to

L17 Vehicles L33 Air transport ⊓ ⊓R37 Soundproofing


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Aeroplanes-Soundproofing From database already established:

Aeroplanes = Airplane [Spelling variant]

ThereforeTerm is recognized as same asAirplanes. Soundproofing

Resolved to



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Any class formed by geographical subdivision

Such as

NA6300-6307 Airport buildings

NA6305.E3 Egypt

Recognized using a dictionary of geographical names

Inherits from subject class above it; simply add the country

L15 Traffic stations L33 Air transport ⊓ P23 Buildings T77 Civilian ⊓ ⊓ ⊓

Egypt

No editor checking needed


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Examples from the resulting knowledge base

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HE550-560 Ports, harbors, docks, wharves, etc.

NA2800 Architectural acoustics

NA6300-6307 Airport buildings

NA6330 Dock buildings, ferry houses, etc.

TC350-374 Harbor works

TH1725 Soundproof construction

TL681.S6 Airplanes. Soundproofing

TL725-726 Airways (Routes). Airports and landing fields. Aerodromes

VA67-79 Naval ports, bases, reservations, docks

VM367.S6 Submarines. Soundproofing

= L15 Traffic stations L37 Water transport ⊓ T77 Civilian⊓

= P27 Architecture R30 Acoustics⊓

= L15 Traffic stations L33 Air transport ⊓ ⊓P23 Buildings T77 Civilian⊓

= L15 Traffic stations L37 Water transport ⊓ P23 Buildings T77 Civilian⊓ ⊓

= L15 Traffic stations L37 Water transport ⊓ R00 Engineering T77 Civilian⊓ ⊓

= P23 Buildings P43 Construction ⊓ ⊓R37 Soundproofing

= L17 Vehicles L33 Air transport ⊓ ⊓R37 Soundproofing

= L13 Traffic facilities L33 Air transport ⊓ ⊓Technical aspects

= L15 Traffic stations L37 Water transport ⊓ T73 Military⊓

= L17 Vehicles L37 Water transport ⊓ ⊓R37 Soundproofing T73 Military ⊓ ⊓Underwater

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Aeroplanes-Soundproofing

Airports-Buildings

Buildings-Soundproofing

Ships-Soundproofing

= L17 Vehicles L33 Air transport ⊓ ⊓R37 Soundproofing

= P23 Buildings L15 Traffic stations ⊓ ⊓L33 Air transport

= P23 Buildings P43 Construction ⊓ ⊓R37 Soundproofing

= L17 Vehicles L37 Water transport ⊓ ⊓R37 Soundproofing

LC subject headings with combinations of atomic concepts

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Hub


L17 Vehicles ⊓ L37 Water transport ⊓ R37 Soundproofing

L17 Vehicles ⊓ L37 Water transport ⊓ R37 Soundproofing T73 ⊓Military⊓ Underwater

LCC



LCSH


Ships-Soundproofing


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Hub

Canonical form of query

(DL formula)

User query

Free text

Combination of elemental concepts through facets (guided query formulation)

Controlled term(s) from a KOS, possibly found through browsing a KOS

Final query

(Enriched) free text query

Query in terms of a KOS

Mapping user queries

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Ships-Soundproofing

[L17 Vehicles L33 Air transport ⊓ ⊓R37 Soundproofing]

[L17 Vehicles L37 Water transport ⊓ ⊓R37 Soundproofing Military]⊓

[L17 Vehicles L33 Air transport ⊓ ⊓R37 Soundproofing]

[L17 Vehicles L37 Water transport ⊓ ⊓R37 Soundproofing]

Query:L17 Vehicles AND R37

Soundproofing

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Examples from NALT and LCSH

• NALT National Agricultural Library Thesaurus

• LCSH Library of Congress Subject Headings

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Air pollution laws

LCSH term

Air – Pollution – Laws and regulations

[isa] Legal rule [appliedTo] {[isa] Condition [isConditionOf] Air [causedBy] Pollutant [property] Undesirable}

NALT terms

Air pollution

[isa] Condition [isConditionOf] Air [causedBy] Pollutant [property] Undesirable

Laws and regulations

[isa] Legal rule

Mapping LCSH ▬► NALT

Air – Pollution – Laws and regulations ▬► Air pollution AND

Laws and regulations

Interpretation for indexing and searching in both directions

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Soil moisture vs. Soil water

LCSH term

Soil moisture

[isa] Water [containedIn] Soil

NALT term

Soil water

[isa] Water [containedIn] Soil


Soil moisture ▬► Soil water

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Greenhouse gardening

LCSH term

Greenhouse gardening

[isa] Gardening [inEnvironment] Greenhouse [inEnvironment] Home

NALT terms

Home gardening

[isa] Gardening [inEnvironment] Home

Greenhouse

[isa] Greenhouse


Greenhouse gardening ▬► Home gardening AND

Greenhouse

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Salad greens

LCSH term

Salad greens

[isa] Green leafy vegetable [usedFor] Salad

NALT term

Green leafy vegetables

[isa] Green leafy vegetable


Salad greens ▬► BT Green leafy vegetables

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Emerging diseases

LCSH term

Emerging infectious diseases

[isa] Disease [hasProperty] Infectious [hasProperty] Emerging

NALT term

Emerging diseases

[isa] Disease [hasProperty] Infectious ??? [hasProperty] Emerging


Emerging infectious diseases ▬► Emerging diseases

Emerging infectious diseases ▬► BT Emerging diseases

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Distributed implementation

• A KOS on the Web could assign DL formulas to its concepts − let's call this a semantically enhanced KOS or SEKOS

• Could use any of a number of faceted core classifications or even several (using a unique URI for each elemental concept)

• Core classifications could be mapped to each other

• It is now a simple matter to map from any SEKOS to any other (somewhat dependent on the core classifications used)

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Take-home message

Semantics gives powerful systems

Semantik schafft maechtige Systeme

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L

• C

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This project will achieve the followingInteroperability between any two participating Knowledge Organization Systems (KOS) (to the extent the two schemes allow)Facet-based search

for any collection indexed by a participating KOSfor free-text search

Assistance in cataloging (metadata creation) by catalogers or users (social tagging)Long-range goal: Web service where a KOS can be uploaded and mappings to specified target KOS are returned

MeansCreate a comprehensive knowledge base relating many classification schemes and subject heading lists used in libraries and in other contexts (LCC, DDC, DMOZ directory, LCSH, European schemes).Use combinations of atomic concepts taken from a well-structured underlying faceted classification to represent the meaning of classes and subject headings.

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33

Hub

Water transport


Ocean transport




Dewey





387.1 Ports

LCSH

Shipping


Merchant marine

Harbors

GermanHafen


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HubLCC

LCSH


Koeln 20090706• Themen• Role indicators for building themes• arrangement of themes for exploration under user control• carry-over from citation order• Practical problem of connection to the participating systems – should use IDs for

combinations in Hub. Make sure that hub stays consistent with participating systems.

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Documents

Semantic Mapping through a concept hub Dagobert Soergel College of Information Studies, University of Maryland Department of Library and Information Studies,