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

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Presentation on theme: "Semantic Mapping through a concept hub Dagobert Soergel College of Information Studies, University of Maryland Department of Library and Information Studies,"— Presentation transcript:

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

2 2 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 Ocean transportation Inland waterway tr. > Ports Ports LCSH Shipping Inland water transport Merchant marine Harbors German Hafen Mapping through a Hub

3 3 Outline Objective: Interoperability Plus KOS concept hub Method: Knowledge-based, computer-assisted of canonical representations of concepts Resulting knowledge base and applications

4 4 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

5 5 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

6 6 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 Ocean transportation Inland waterway tr. > Ports Ports LCSH Shipping Inland water transport Merchant marine Harbors German Hafen Mapping through a Hub

7 7 Method: How to get DL formulas Key: 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

8 8 Knowledge base Requires an ever larger classification and lexical knowledge base containing many kinds of data: 1.A faceted classification of atomic concepts Seeded 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.

9 9 Examples of deriving DL formulas

10 10 L00Transportation and traffic L10Traffic system components L13Traffic facilities L15Traffic stations L17Vehicles L30Modes of transportation L33Air transport L37Water transport P00Buildings, construction P23Buildings P27Architecture P43Construction R00Engineering R30Acoustics R37Soundproofing T70Military vs. civilian T73Military T77Civilian Underlying faceted classification

11 11 HE Transportation HE 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

12 12 NA Airport buildingsFrom 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 Method: Assigning atomic concepts 2

13 13 TL681.S6 Airplanes. SoundproofingFrom 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 Method: Assigning atomic concepts 3

14 14 Aeroplanes-SoundproofingFrom database already established: Aeroplanes = Airplane [Spelling variant] Therefore Term is recognized as same as Airplanes. Soundproofing Resolved to L17 Vehicles L33 Air transport R37 Soundproofing Method: Assigning atomic concepts 4

15 15 Any class formed by geographical subdivision Such as NA 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 Method: Assigning atomic concepts 5

16 16 Examples from the resulting knowledge base

17 17 HE Ports, harbors, docks, wharves, etc. NA2800 Architectural acoustics NA Airport buildings NA6330 Dock buildings, ferry houses, etc. TC Harbor works TH1725 Soundproof construction TL681.S6 Airplanes. Soundproofing TL 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

18 18 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

19 19 Hub L17 Vehicles L33 Air transport R37 Soundproofing L17 Vehicles L37 Water transport R37 Soundproofing L17 Vehicles L37 Water transport R37 Soundproofing T73 Military Underwater LCC TL681.S6 Airplanes. Soundproofing VM367.S6 Submarines. Soundproofing LCSH Aeroplanes- Soundproofing Ships-Soundproofing Mapping through a Hub

20 20 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

21 21 TL681.S6 Airplanes. Soundproofing VM367.S6 Submarines. Soundproofing Aeroplanes-Soundproofing 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

22 22 Examples from NALT and LCSH NALTNational Agricultural Library Thesaurus LCSHLibrary of Congress Subject Headings

23 23 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

24 24 Soil moisture vs. Soil water LCSH term Soil moisture [isa] Water [containedIn] Soil NALT term Soil water [isa] Water [containedIn] Soil Mapping LCSH NALT Soil moisture Soil water

25 25 Greenhouse gardening LCSH term Greenhouse gardening [isa] Gardening [inEnvironment] Greenhouse [inEnvironment] Home NALT terms Home gardening [isa] Gardening [inEnvironment] Home Greenhouse [isa] Greenhouse Mapping LCSH NALT Greenhouse gardening Home gardening AND Greenhouse

26 26 Salad greens LCSH term Salad greens [isa] Green leafy vegetable [usedFor] Salad NALT term Green leafy vegetables [isa] Green leafy vegetable Mapping LCSH NALT Salad greens BT Green leafy vegetables

27 27 Emerging diseases LCSH term Emerging infectious diseases [isa] Disease [hasProperty] Infectious [hasProperty] Emerging NALT term Emerging diseases [isa] Disease [hasProperty] Infectious ??? [hasProperty] Emerging Mapping LCSH NALT Emerging infectious diseases Emerging diseases Emerging infectious diseases BT Emerging diseases

28 28 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)

29 29 Take-home message Semantics gives powerful systems Semantik schafft maechtige Systeme

30 30 L C

31 31 This project will achieve the following Interoperability 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 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 Means Create 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.

32 32

33 33 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 Ocean transportation Inland waterway tr. > Ports Ports LCSH Shipping Inland water transport Merchant marine Harbors German Hafen Mapping through a Hub

34 34 Hub LCC LCSH Mapping through a Hub

35 Koeln 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. 35


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