New Ways of Mapping Knowledge Organization Systems: Using a Semi-Automatic Matching Procedure for Building up Vocabulary Crosswalks.

Saved in:
Bibliographic Details
Title: New Ways of Mapping Knowledge Organization Systems: Using a Semi-Automatic Matching Procedure for Building up Vocabulary Crosswalks.
Authors: Kempf, Andreas Oskar1 andreas.kempf@gesis.org, Ritze, Dominique2 dominique.ritze@bib.uni-mannheim.de, Eckert, Kai3 kai@informatik.uni-mannheim.de, Zapilko, Benjamin1 benjamin.zapilko@gesis.org
Source: Knowledge Organization. 2014, Vol. 41 Issue 1, p66-75. 10p.
Subjects: Knowledge management, Metadata mapping, Vocabulary, Metadata, Subject headings
Abstract: Crosswalks between different vocabularies are an indispensable prerequisite for integrated, high-quality search scenarios in distributed data environments where more than one controlled vocabulary is in use. Offered through the web and linked with each other they act as a central link so that users can move back and forth between different online data sources. In the past, crosswalks between different thesauri have usually been developed manually. In the long run the intellectual updating of such crosswalks is expensive. An obvious solution would be to apply automatic matching procedures, such as the so-called ontology matching tools. On the basis of computer- generated correspondences between the Thesaurus for the Social Sciences (TSS) and the Thesaurus for Economics (STW), our contribution explores the trade-off between IT-assisted tools and procedures on the one hand and external quality evaluation by domain experts on the other hand. This paper presents techniques for semi-automatic development and maintenance of vocabulary crosswalks. The performance of multiple matching tools was first evaluated against a reference set of correct mappings, then the tools were used to generate new mappings. It was concluded that the ontology matching tools can be used effectively to speed up the work of domain experts. By optimizing the workflow, the method promises to facilitate sustained updating of high-quality vocabulary crosswalks [ABSTRACT FROM AUTHOR]
Copyright of Knowledge Organization is the property of IMR Press and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
FullText Links:
  – Type: pdflink
Text:
  Availability: 0
Header DbId: egs
DbLabel: Engineering Source
An: 93913696
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: New Ways of Mapping Knowledge Organization Systems: Using a Semi-Automatic Matching Procedure for Building up Vocabulary Crosswalks.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Kempf%2C+Andreas+Oskar%22">Kempf, Andreas Oskar</searchLink><relatesTo>1</relatesTo><i> andreas.kempf@gesis.org</i><br /><searchLink fieldCode="AR" term="%22Ritze%2C+Dominique%22">Ritze, Dominique</searchLink><relatesTo>2</relatesTo><i> dominique.ritze@bib.uni-mannheim.de</i><br /><searchLink fieldCode="AR" term="%22Eckert%2C+Kai%22">Eckert, Kai</searchLink><relatesTo>3</relatesTo><i> kai@informatik.uni-mannheim.de</i><br /><searchLink fieldCode="AR" term="%22Zapilko%2C+Benjamin%22">Zapilko, Benjamin</searchLink><relatesTo>1</relatesTo><i> benjamin.zapilko@gesis.org</i>
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%22Knowledge+Organization%22">Knowledge Organization</searchLink>. 2014, Vol. 41 Issue 1, p66-75. 10p.
– Name: Subject
  Label: Subjects
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Knowledge+management%22">Knowledge management</searchLink><br /><searchLink fieldCode="DE" term="%22Metadata+mapping%22">Metadata mapping</searchLink><br /><searchLink fieldCode="DE" term="%22Vocabulary%22">Vocabulary</searchLink><br /><searchLink fieldCode="DE" term="%22Metadata%22">Metadata</searchLink><br /><searchLink fieldCode="DE" term="%22Subject+headings%22">Subject headings</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Crosswalks between different vocabularies are an indispensable prerequisite for integrated, high-quality search scenarios in distributed data environments where more than one controlled vocabulary is in use. Offered through the web and linked with each other they act as a central link so that users can move back and forth between different online data sources. In the past, crosswalks between different thesauri have usually been developed manually. In the long run the intellectual updating of such crosswalks is expensive. An obvious solution would be to apply automatic matching procedures, such as the so-called ontology matching tools. On the basis of computer- generated correspondences between the Thesaurus for the Social Sciences (TSS) and the Thesaurus for Economics (STW), our contribution explores the trade-off between IT-assisted tools and procedures on the one hand and external quality evaluation by domain experts on the other hand. This paper presents techniques for semi-automatic development and maintenance of vocabulary crosswalks. The performance of multiple matching tools was first evaluated against a reference set of correct mappings, then the tools were used to generate new mappings. It was concluded that the ontology matching tools can be used effectively to speed up the work of domain experts. By optimizing the workflow, the method promises to facilitate sustained updating of high-quality vocabulary crosswalks [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Knowledge Organization is the property of IMR Press and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=93913696
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.5771/0943-7444-2014-1-66
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 10
        StartPage: 66
    Subjects:
      – SubjectFull: Knowledge management
        Type: general
      – SubjectFull: Metadata mapping
        Type: general
      – SubjectFull: Vocabulary
        Type: general
      – SubjectFull: Metadata
        Type: general
      – SubjectFull: Subject headings
        Type: general
    Titles:
      – TitleFull: New Ways of Mapping Knowledge Organization Systems: Using a Semi-Automatic Matching Procedure for Building up Vocabulary Crosswalks.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Kempf, Andreas Oskar
      – PersonEntity:
          Name:
            NameFull: Ritze, Dominique
      – PersonEntity:
          Name:
            NameFull: Eckert, Kai
      – PersonEntity:
          Name:
            NameFull: Zapilko, Benjamin
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 01
              Text: 2014
              Type: published
              Y: 2014
          Identifiers:
            – Type: issn-print
              Value: 09437444
          Numbering:
            – Type: volume
              Value: 41
            – Type: issue
              Value: 1
          Titles:
            – TitleFull: Knowledge Organization
              Type: main
ResultId 1