Search (4 results, page 1 of 1)

0.008224075 = product of:
  0.049344447 = sum of:
    0.049344447 = weight(_text_:b in 3392) [ClassicSimilarity], result of:
      0.049344447 = score(doc=3392,freq=4.0), product of:
        0.14855953 = queryWeight, product of:
          3.542962 = idf(docFreq=3476, maxDocs=44218)
          0.041930884 = queryNorm
        0.3321527 = fieldWeight in 3392, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          3.542962 = idf(docFreq=3476, maxDocs=44218)
          0.046875 = fieldNorm(doc=3392)
  0.16666667 = coord(1/6)

Abstract

Im August 2009 wurde SKOS "Simple Knowledge Organization System" als neuer Standard für web-basierte kontrollierte Vokabulare durch das W3C veröffentlicht1. SKOS dient als Datenmodell, um kontrollierte Vokabulare über das Web anzubieten sowie technisch und semantisch interoperabel zu machen. Perspektivisch kann die heterogene Landschaft der Erschließungsvokabulare über SKOS vereinheitlicht und vor allem die Inhalte der klassischen Datenbanken (Bereich Fachinformation) für Anwendungen des Semantic Web, beispielsweise als Linked Open Data2 (LOD), zugänglich und stär-ker miteinander vernetzt werden. Vokabulare im SKOS-Format können dabei eine relevante Funktion einnehmen, indem sie als standardisiertes Brückenvokabular dienen und semantische Verlinkung zwischen erschlossenen, veröffentlichten Daten herstellen. Die folgende Fallstudie skizziert ein Szenario mit drei thematisch verwandten Thesauri, die ins SKOS-Format übertragen und inhaltlich über Crosskonkordanzen aus dem Projekt KoMoHe verbunden werden. Die Mapping Properties von SKOS bieten dazu standardisierte Relationen, die denen der Crosskonkordanzen entsprechen. Die beteiligten Thesauri der Fallstudie sind a) TheSoz (Thesaurus Sozialwissenschaften, GESIS), b) STW (Standard-Thesaurus Wirtschaft, ZBW) und c) IBLK-Thesaurus (SWP).

0.0058152988 = product of:
  0.03489179 = sum of:
    0.03489179 = weight(_text_:b in 38) [ClassicSimilarity], result of:
      0.03489179 = score(doc=38,freq=2.0), product of:
        0.14855953 = queryWeight, product of:
          3.542962 = idf(docFreq=3476, maxDocs=44218)
          0.041930884 = queryNorm
        0.23486741 = fieldWeight in 38, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.542962 = idf(docFreq=3476, maxDocs=44218)
          0.046875 = fieldNorm(doc=38)
  0.16666667 = coord(1/6)

0.004797377 = product of:
  0.028784262 = sum of:
    0.028784262 = weight(_text_:b in 542) [ClassicSimilarity], result of:
      0.028784262 = score(doc=542,freq=4.0), product of:
        0.14855953 = queryWeight, product of:
          3.542962 = idf(docFreq=3476, maxDocs=44218)
          0.041930884 = queryNorm
        0.19375575 = fieldWeight in 542, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          3.542962 = idf(docFreq=3476, maxDocs=44218)
          0.02734375 = fieldNorm(doc=542)
  0.16666667 = coord(1/6)

Abstract

In 2004, the German Federal Ministry for Education and Research funded a major terminology mapping initiative at the GESIS Social Science Information Centre in Bonn (GESIS-IZ), which will find its conclusion this year. The task of this terminology mapping initiative was to organize, create and manage 'crossconcordances' between major controlled vocabularies (thesauri, classification systems, subject heading lists) centred around the social sciences but quickly extending to other subject areas. Cross-concordances are intellectually (manually) created crosswalks that determine equivalence, hierarchy, and association relations between terms from two controlled vocabularies. Most vocabularies have been related bilaterally, that is, there is a cross-concordance relating terms from vocabulary A to vocabulary B as well as a cross-concordance relating terms from vocabulary B to vocabulary A (bilateral relations are not necessarily symmetrical). Till August 2007, 24 controlled vocabularies from 11 disciplines will be connected with vocabulary sizes ranging from 2,000 - 17,000 terms per vocabulary. To date more than 260,000 relations are generated. A database including all vocabularies and cross-concordances was built and a 'heterogeneity service' developed, a web service, which makes the cross-concordances available for other applications. Many cross-concordances are already implemented and utilized for the German Social Science Information Portal Sowiport (www.sowiport.de), which searches bibliographical and other information resources (incl. 13 databases with 10 different vocabularies and ca. 2.5 million references).

0.0038768656 = product of:
  0.023261193 = sum of:
    0.023261193 = weight(_text_:b in 250) [ClassicSimilarity], result of:
      0.023261193 = score(doc=250,freq=2.0), product of:
        0.14855953 = queryWeight, product of:
          3.542962 = idf(docFreq=3476, maxDocs=44218)
          0.041930884 = queryNorm
        0.15657827 = fieldWeight in 250, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.542962 = idf(docFreq=3476, maxDocs=44218)
          0.03125 = fieldNorm(doc=250)
  0.16666667 = coord(1/6)