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Organizing and implementing on the thesauri mapping project
 

Organizing and implementing on the thesauri mapping project

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    Organizing and implementing on the thesauri mapping project Organizing and implementing on the thesauri mapping project Presentation Transcript

    • Organizing and Implementing on the Thesauri Mapping Project Dr. Chang Chun Associate Professor Agriculture Information Institute, Chinese Academy of Agricultural Sciences (AII/CAAS), Beijing China The Seventh Agricultural Ontology Service (AOS) Workshop AFITA 2006 November 9-11, Bangalore, India
    • Outline
      • Introduction
      • Organizing
      • AGROVOC and CAT
      • Conclusions
      Outline 7 th AOS
      • Objectives
      • Methods
      • Mapping rules
      • Discussions
    • Brief Introduction on the Mapping Project CAT CAAS AGROVOC FAO ExactMatch InexactMatch BroadMatch NarrowMatch AND,OR,NOT No mapping mapping mapping Mapping Rules Resource Target 7 th AOS Introduction
    • Objective 1: Enrich AOS Terminology Domain Knowledge
      • Key words have problems in search information;
      • Thesauri are still working in information management;
      • Research on conversion from thesaurus to ontology;
      • Mapping can add more new domain knowledge.
      7 th AOS Objective
    • Objective 2: Develop Cross-Language Search System 7 th AOS Objective Chinese users Mapping Information ( e, b,n… ) Chinese data AGRIS data AGROVOC CAT English Users Search Search Search end Search end
    • The Time and Tools of Mapping Project
      • The time of mapping project: From September 2005 to September 2006;
      • Mapping rules: a revision method of SKOS Mapping Vocabulary Specification;
      • Mapping direction: from CAT (resource) to AGROVOC (target)
      • Mapping tools: Protégé , Excel sheet, CAT and AGROVOC CD-ROM.
      7 th AOS Organizing
    • Working Flow
      • From 2005-09-01 to 2005-11-05: make plans of mapping methods, prepare and test the mapping data;
      • From 2005-11-06 to 2006-05-30: the training and mapping with Excel sheet;
      • From 2006-06-01 to 2006-09-30: convert the Excel sheet information to OWL mapping data, Protégé can read this information.
      7 th AOS Organizing
    • The specialists
      • we organized about 16 agricultural domain specialists in CAAS, many of them are PhD students, they were chosen based on the domain.
      • The main domain are biological science, agricultural environmental science, agricultural meteorology, fertilizer science, horticulture, forestry practice, plant protection, agronomy, agricultural products processing and storage and comprehensive utilization, veterinary medicine, biological control, Industrial technology and equipment, fishery science, and so on.
      • Some of them have knowledge of thesaurus.
      7 th AOS Organizing
    • AGROVOC and CAT
      • AGROVOC :
        • 27736 English terms: 16769 descriptors , 10967 non descriptors
        • 25060 Chinese terms: 16628 descriptors , 8432 non descriptors
        • 1240 top terms
        • organized in 130 categories (AGRIS/CARIS)
        • includes biological taxonomy and geographical names
      • CAT :
        • 64638 Chinese terms: 51614 descriptors, 13024 non-descriptors
        • 51400 descriptors has at least one translation
        • 2332 top terms
        • organized in 40 categories (e.g. crops, etc.)
        • includes biological taxonomy and geographical names
      7 th AOS Organizing
    • To Finish the Mapping Work in Two Steps
      • First, Excel sheet:
      • We split CAT into 36 documents based on the domain, we use Excel sheet, try to find all mapping information and input it in the Excel sheet, all these sheets will be kept as original data;
      • Second,convert information to OWL document:
      • After we finish the all Excel sheets, we convert and input these mapping information into OWL documents, they can be read in Protégé after import CAT and AGROVOC.
      7 th AOS Organizing
    • Excel sheets 7 th AOS Organizing A B C D E F G H I J C-term code C- term Relation A-term code A- term combine relation C-revise suggestion C- comment A-revise suggestion A- comment
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    • Mapping Standards and Methods
      • Exact Match, Inexact Match ;
      • Broad Match,Narrow Match ;
      • AND ; OR ; NOT ;
      7 th AOS Methods
    • Mapping relationships
      • Exact match
        • SKOS: exactMatch
        • OWL: equivalentTo
      • Broader/Narrower match
        • SKOS: broadMatch, narrowMatch
        • OWL: subClassOf
      • OR, AND, NOT operators
        • SKOS: OR, AND, NOT
        • OWL unionOf, intersectionOf, complementOf
      • Partial equivalences
        • SKOS: minorMatch, majorMatch
      7 th AOS Methods
    • Exact Match CAT AGROVOC Mapping Exact Match Such as :‘ 17147- 禾谷类作物’ Exact Match ‘25512-Cereal crops’ 7 th AOS Methods
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    • equivalentClass: One of main mapping relation (13105) <rdf:Description rdf:about=&quot;http://www.caas.net.cn/2005/cat#c_17147_ 禾谷类作物 _Cerealcrop&quot;> <owl:equivalentClass> <rdf:Description rdf:about=&quot;http://www.fao.org/aos/agrovoc/2005#c_25512_Cerealcrops_ 禾谷类作物 &quot;> <owl:equivalentClass rdf:resource=&quot;http://www.caas.net.cn/2005/cat#c_17147_ 禾谷类作物 _Cerealcrop&quot;/> </rdf:Description> </owl:equivalentClass> </rdf:Description> 7 th AOS Methods
    • Inexact Match CAT Mapping AGROVOC Inexact Such as :‘经济大国’ Inexact match ‘Developed countries’ 7 th AOS Methods
    • Inexact Match : We seldom use this mapping relation 55581_ 玉米芯 _Maizecob ie 16171 <rdf:Description rdf:about=&quot;http://www.caas.net.cn/2005/cat#c_55581_ 玉米芯 _Maizecob&quot;> <rdfs:comment rdf:datatype=&quot;http://www.w3.org/2001/XMLSchema#string&quot; >inexact mapping with 16171</rdfs:comment> </rdf:Description> 7 th AOS Methods
    • Broad Match CAT Mapping AGROVOC Broad Match Such as :“ 35234- 普及教育” Broad Match ‘2488-Education’ 7 th AOS Methods
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    • subClassOf: BroadMatch (another main mapping relation 11408) <rdf:Description rdf:about=&quot;http://www.caas.net.cn/2005/cat#c_35234_ 普及教育 _Universaleducation&quot;> <rdfs:subClassOf rdf:resource=&quot;http://www.fao.org/aos/agrovoc/2005#c_2488_Education_ 教育 &quot;/> </rdf:Description> 7 th AOS Methods
    • Narrow Match CAT Mapping AGROVOC Narrow Match Such as : “ 8341_ 岛屿 _Islands” Narrow Match “695_Atolls_ 环礁” 7 th AOS Methods
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    • subClassOf: Narrow Match (173) <rdf:Description rdf:about=&quot;http://www.fao.org/aos/agrovoc/2005#c_695_Atolls_ 环礁 &quot;> <rdfs:subClassOf rdf:resource=&quot;http://www.caas.net.cn/2005/cat#c_8341_ 岛屿 _Islands&quot;/> </rdf:Description> 7 th AOS Methods
    • AND ; OR ; NOT AND “ 59683- 自动标引” Exact Match ‘11729-Indexing of information’ AND ‘15855 -Automation’ OR NOT “ 7536_ 大麦 _Barley” Exact Match ‘823_Barley_ 大麦 OR 3662_Hordeum vulgare_ 大麦植物’ ‘ 12114- 非传染性病害’ Exact match ‘5962-Plant diseases’ NOT ‘34024-Infectious diseases’ 7 th AOS Methods
    • AND “ 59683_ 自动标引 _Automaticindexing” Exact Match 11729_Indexingofinformation_ 信息编目 and 15855_Automation_ 自动化 7 th AOS Methods
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    • AND: intersectionOf <owl:Class> <owl:intersectionOf rdf:parseType=&quot;Collection&quot;> <rdf:Description rdf:about=&quot;http://www.fao.org/aos/agrovoc/2005#c_11729_Indexingofinformation_ 信息编目 &quot;/> <rdf:Description rdf:about=&quot;http://www.fao.org/aos/agrovoc/2005#c_15855_Automation_ 自动化 &quot;/> </owl:intersectionOf> </owl:Class> <rdf:Description rdf:about=&quot;http://www.caas.net.cn/2005/cat#c_59683_ 自动标引 _Automaticindexing&quot;> <owl:equivalentClass> <owl:Class> <owl:intersectionOf rdf:parseType=&quot;Collection&quot;> <rdf:Description rdf:about=&quot;http://www.fao.org/aos/agrovoc/2005#c_11729_Indexingofinformation_ 信息编目 &quot;/> <rdf:Description rdf:about=&quot;http://www.fao.org/aos/agrovoc/2005#c_15855_Automation_ 自动化 &quot;/> </owl:intersectionOf> </owl:Class> </owl:equivalentClass> </rdf:Description> 7 th AOS Methods
    • OR 7536_ 大麦 _Barley” Exact Match ‘ 823_Barley_ 大麦 OR 3662_Hordeum vulgare_ 大麦植物 Methods 7 th AOS
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    • OR: unionOf <owl:Class> <owl:unionOf rdf:parseType=&quot;Collection&quot;> <rdf:Description rdf:about=&quot;http://www.fao.org/aos/agrovoc/2005#c_823_Barley_ 大麦 &quot;/> <rdf:Description rdf:about=&quot;http://www.fao.org/aos/agrovoc/2005#c_3662_Hordeumvulgare_ 大麦植物 &quot;/> </owl:unionOf> </owl:Class> <rdf:Description rdf:about=&quot;http://www.caas.net.cn/2005/cat#c_7536_ 大麦 _Barley&quot;> <owl:equivalentClass> <owl:Class> <owl:unionOf rdf:parseType=&quot;Collection&quot;> <rdf:Description rdf:about=&quot;http://www.fao.org/aos/agrovoc/2005#c_823_Barley_ 大麦 &quot;/> <rdf:Description rdf:about=&quot;http://www.fao.org/aos/agrovoc/2005#c_3662_Hordeumvulgare_ 大麦植物 &quot;/> </owl:unionOf> </owl:Class> </owl:equivalentClass> </rdf:Description> 7 th AOS Methods
    • NOT ‘ 12114_ 非传染性病害 _Non-infectiousdiseases’ Exact match ‘5962_Plantdiseases_ 植物病害 ’ AND NOT ‘34024_Infectiousdiseases_ 侵染性病害’ 7 th AOS Methods
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    • NOT: complementOf <owl:Class> <owl:intersectionOf rdf:parseType=&quot;Collection&quot;> <rdf:Description rdf:about=&quot;http://www.fao.org/aos/agrovoc/2005#c_5962_Plantdiseases_ 植物病害 &quot;/> <owl:Class> <owl:complementOf rdf:resource=&quot;http://www.fao.org/aos/agrovoc/2005#c_34024_Infectiousdiseases_ 侵染性病害 &quot;/> </owl:Class> </owl:intersectionOf> </owl:Class> <rdf:Description rdf:about=&quot;http://www.caas.net.cn/2005/cat#c_12114_ 非传染性病害 _Non-infectiousdiseases&quot;> <owl:equivalentClass> <owl:Class> <owl:intersectionOf rdf:parseType=&quot;Collection&quot;> <rdf:Description rdf:about=&quot;http://www.fao.org/aos/agrovoc/2005#c_5962_Plantdiseases_ 植物病害 &quot;/> <owl:Class> <owl:complementOf rdf:resource=&quot;http://www.fao.org/aos/agrovoc/2005#c_34024_Infectiousdiseases_ 侵染性病害 &quot;/> </owl:Class> </owl:intersectionOf> </owl:Class> </owl:equivalentClass> </rdf:Description> 7 th AOS Methods
    • No mapping: 13867_ 干扰 _Interference 7 th AOS Methods
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    • NoMapping: comment <rdf:Description rdf:about=&quot;http://www.caas.net.cn/2005/cat#c_13867_ 干扰 _Interference&quot;> <rdfs:comment rdf:datatype=&quot;http://www.w3.org/2001/XMLSchema#string&quot; >AGROVOC hasn't this concept</rdfs:comment> </rdf:Description> 7 th AOS Methods
    • How to get OWL documents
      • Convert the Excel sheet information to Protégé (machine convert and human input ), and get OWL mapping data;
      • Use the tools of ‘import ontology’, import one domain of CAT and whole AGROVOC, and input the mapping relations, after save the working, we can get different domain OWL documents;
      7 th AOS Methods
    • Combine the OWL documents
      • Delete the top and the end of all OWL documents, then paste them together,we get the whole middle part of mapping project;
      • Create a new OWL document, import whole CAT and AGROVOC, and save the document;
      • Insert the whole middle part of mapping project into the upper document, then we get a whole mapping OWL document, it works with whole CAT and AGROVOC.
      Methods 7 th AOS
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    • 1 Candidate and the True mapping Conclusions 7 th AOS Automatic identification of candidate exact matches The statistics of true mapping matches relation Classification Exact match b n e-b-n total Other relation Classification total Total 13 105 11 408 173 24 686 1 747 25 433 Tentative exact match 3 890 188 405 3 297 Match Chinese but different English Match not ensured 1 187 15 546 624 Match English but different Chinese Exact match 4 160 143 1 547 2 470 Match English and Chinese Action Total Geogr . Taxon. Num.
    • 2 The Series Mapping Knowledge Data Files Conclusions 7 th AOS The contribution include the following documents: (a)    cat_agrovco_mapping.owl; (b)    ag_20051101.owl; (c)    cat_all_u.owl; (d)    agrovoc-zh-revise.xls; (e)    agrovoc-usefor-comment.xls; Users can use Protégé create a new ontology with the data of (a), the machine will ask to import (b) and (c), and then you can open the (a), the open time is a little slow, our computer need about 4 minutes, the computer CPU 3.4, RAM: 1 G. (d) notes the information which need to be revised about the terms of AGROVOC; (e) is the comments about AGROVOC terms
    • Discussions
      • No mapping ;
      • InexactMatch;
      • Begin from the top term;
      • Mapping document need work with CAT and AGROVOC;
      • There are many broadMatch relations;
      • The comment and the suggestion;
      7 th AOS Discussions
    • The Heredity of Mapping Relation
      • About 60% CAT concepts obtain mapping relation with AGROVOC by heredity. They normally follow the ExactMatch, BroadMatch (24 513)
      7 th AOS Discussions C1 A1 21 22 31 32 33 ExactMatch BroadMatch CAT AGROVOC
    • Different Thesauri with Different Classification
      • A few concepts have different domain trees in two thesauri, means different thesauri have their own classification.
      7 th AOS Discussions C1 A1 21 22 31 32 33 ExactMatch CAT AGROVOC 21 22 31 32
    • The Resource and Target
      • ExactMatch: same concepts;
      • BroadMatch: Chinese users get more broad concept, or get some useless information;English users get more specific concept, or can’t find all information.
      • NarrowMatch: the opposite.
      • CAT has more than 60,000 terms, AGROVOC has only about 30,000 terms, so take CAT as resource is better.
      7 th AOS Discussions C1 A1 21 22 31 32 33 ExactMatch BroadMatch CAT AGROVOC A4 NarrowMatch
    • Discussions 2
      • Different knowledge taxonomy ;
      • Difference on noun and verb ;
      • Different social ideas ;
      • Different cultures ;
      • Different translations.
      7 th AOS Discussions
    • Chinese Academy of Agricultural Sciences (CAAS) and Food and Agriculture Organization (FAO) changc@mail.caas.net.cn [email_address] Thank you 7 th AOS Thanks