Search (3 results, page 1 of 1)

0.0054827165 = product of:
  0.0328963 = sum of:
    0.0328963 = weight(_text_:b in 3137) [ClassicSimilarity], result of:
      0.0328963 = score(doc=3137,freq=4.0), product of:
        0.14855953 = queryWeight, product of:
          3.542962 = idf(docFreq=3476, maxDocs=44218)
          0.041930884 = queryNorm
        0.22143513 = fieldWeight in 3137, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          3.542962 = idf(docFreq=3476, maxDocs=44218)
          0.03125 = fieldNorm(doc=3137)
  0.16666667 = coord(1/6)

Abstract

"Thomson Reuters' citation indexes i.e. SCI, SSCI and AHCI are said to be "authoritative". Due to the huge influence of these databases on global academic evaluation of productivity and impact, Terje Tüür-Fröhlich decided to conduct case studies on the data quality of Social Sciences Citation Index (SSCI) records. Tüür-Fröhlich investigated articles from social science and law. The main findings: SSCI records contain tremendous amounts of "trivial errors", not only misspellings and typos as previously mentioned in bibliometrics and scientometrics literature. But Tüür-Fröhlich's research documented fatal errors which have not been mentioned in the scientometrics literature yet at all. Tüür-Fröhlich found more than 80 fatal mutations and mutilations of Pierre Bourdieu (e.g. "Atkinson" or "Pierre, B. and "Pierri, B."). SSCI even generated zombie references (phantom authors and works) by data fields' confusion - a deadly sin for a database producer - as fragments of Patent Laws were indexed as fictional author surnames/initials. Additionally, horrific OCR-errors (e.g. "nuxure" instead of "Nature" as journal title) were identified. Tüür-Fröhlich´s extensive quantitative case study of an article of the Harvard Law Review resulted in a devastating finding: only 1% of all correct references from the original article were indexed by SSCI without any mistake or error. Many scientific communication experts and database providers' believe that errors in databanks are of less importance: There are many errors, yes - but they would counterbalance each other, errors would not result in citation losses and would not bear any effect on retrieval and evaluation outcomes. Terje Tüür-Fröhlich claims the contrary: errors and inconsistencies are not evenly distributed but linked with languages biases and publication cultures."

0.0023671067 = product of:
  0.014202639 = sum of:
    0.014202639 = product of:
      0.028405279 = sum of:
        0.028405279 = weight(_text_:22 in 1935) [ClassicSimilarity], result of:
          0.028405279 = score(doc=1935,freq=2.0), product of:
            0.1468348 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.041930884 = queryNorm
            0.19345059 = fieldWeight in 1935, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.0390625 = fieldNorm(doc=1935)
      0.5 = coord(1/2)
  0.16666667 = coord(1/6)

Date

22. 6.2008 13:03:30

0.0018936852 = product of:
  0.011362111 = sum of:
    0.011362111 = product of:
      0.022724222 = sum of:
        0.022724222 = weight(_text_:22 in 566) [ClassicSimilarity], result of:
          0.022724222 = score(doc=566,freq=2.0), product of:
            0.1468348 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.041930884 = queryNorm
            0.15476047 = fieldWeight in 566, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.03125 = fieldNorm(doc=566)
      0.5 = coord(1/2)
  0.16666667 = coord(1/6)

Content

Section 1 Context and purpose of knowledge architecture -- 1 Making the case for knowledge architecture -- 2 The landscape of knowledge assets -- 3 Knowledge architecture and design -- 4 Knowledge architecture reference model -- 5 Knowledge architecture segments -- Section 2 Designing for availability -- 6 Knowledge object modeling -- 7 Knowledge structures for encoding, formatting, and packaging -- 8 Functional architecture for identification and distinction -- 9 Functional architectures for knowledge asset disposition and destruction -- 10 Functional architecture designs for knowledge preservation and conservation -- Section 3 Designing for accessibility -- 11 Functional architectures for knowledge seeking and discovery -- 12 Functional architecture for knowledge search -- 13 Functional architecture for knowledge categorization -- 14 Functional architectures for indexing and keywording -- 15 Functional architecture for knowledge semantics -- 16 Functional architecture for knowledge abstraction and surrogation -- Section 4 Functional architectures to support knowledge consumption -- 17 Functional architecture for knowledge augmentation, derivation, and synthesis -- 18 Functional architecture to manage risk and harm -- 19 Functional architectures for knowledge authentication and provenance -- 20 Functional architectures for securing knowledge assets -- 21 Functional architectures for authorization and asset management -- Section 5 Pulling it all together - the big picture knowledge architecture -- 22 Functional architecture for knowledge metadata and metainformation -- 23 The whole knowledge architecture - pulling it all together