Search (4 results, page 1 of 1)

  • × author_ss:"Stvilia, B."
  • × year_i:[2000 TO 2010}
  1. Stvilia, B.; Gasser, L.; Twidale, M.B.; Smith, L.C.: ¬A framework for information quality assessment (2007) 0.00 
    0.0030444188 = product of:
  0.0060888375 = sum of:
    0.0060888375 = product of:
      0.012177675 = sum of:
        0.012177675 = weight(_text_:a in 610) [ClassicSimilarity], result of:
          0.012177675 = score(doc=610,freq=18.0), product of:
            0.053105544 = queryWeight, product of:
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.046056706 = queryNorm
            0.22931081 = fieldWeight in 610, product of:
              4.2426405 = tf(freq=18.0), with freq of:
                18.0 = termFreq=18.0
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.046875 = fieldNorm(doc=610)
      0.5 = coord(1/2)
  0.5 = coord(1/2)
    Abstract
    One cannot manage information quality (IQ) without first being able to measure it meaningfully and establishing a causal connection between the source of IQ change, the IQ problem types, the types of activities affected, and their implications. In this article we propose a general IQ assessment framework. In contrast to context-specific IQ assessment models, which usually focus on a few variables determined by local needs, our framework consists of comprehensive typologies of IQ problems, related activities, and a taxonomy of IQ dimensions organized in a systematic way based on sound theories and practices. The framework can be used as a knowledge resource and as a guide for developing IQ measurement models for many different settings. The framework was validated and refined by developing specific IQ measurement models for two large-scale collections of two large classes of information objects: Simple Dublin Core records and online encyclopedia articles.
    Type
    a
  2. Stvilia, B.; Gasser, L.: Value-based metadata quality assessment (2008) 0.00 
    0.0030255679 = product of:
  0.0060511357 = sum of:
    0.0060511357 = product of:
      0.012102271 = sum of:
        0.012102271 = weight(_text_:a in 252) [ClassicSimilarity], result of:
          0.012102271 = score(doc=252,freq=10.0), product of:
            0.053105544 = queryWeight, product of:
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.046056706 = queryNorm
            0.22789092 = fieldWeight in 252, product of:
              3.1622777 = tf(freq=10.0), with freq of:
                10.0 = termFreq=10.0
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.0625 = fieldNorm(doc=252)
      0.5 = coord(1/2)
  0.5 = coord(1/2)
    Abstract
    This article proposes a method that allows a value-based assessment of metadata quality and construction of a baseline quality model. The method is illustrated on a large-scale, aggregated collection of simple Dublin core metadata records. An analysis of the collection suggests that metadata providers and end users may have different value structures for the same metadata. To promote better use of the metadata collection, value models for metadata in the collection should be made transparent to end users and end users should be allowed to participate in content creation and quality control processes.
    Type
    a
  3. Stvilia, B.; Twidale, M.B.; Smith, L.C.; Gasser, L.: Information quality work organization in wikipedia (2008) 0.00 
    0.0025370158 = product of:
  0.0050740317 = sum of:
    0.0050740317 = product of:
      0.010148063 = sum of:
        0.010148063 = weight(_text_:a in 1859) [ClassicSimilarity], result of:
          0.010148063 = score(doc=1859,freq=18.0), product of:
            0.053105544 = queryWeight, product of:
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.046056706 = queryNorm
            0.19109234 = fieldWeight in 1859, product of:
              4.2426405 = tf(freq=18.0), with freq of:
                18.0 = termFreq=18.0
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.0390625 = fieldNorm(doc=1859)
      0.5 = coord(1/2)
  0.5 = coord(1/2)
    Abstract
    The classic problem within the information quality (IQ) research and practice community has been the problem of defining IQ. It has been found repeatedly that IQ is context sensitive and cannot be described, measured, and assured with a single model. There is a need for empirical case studies of IQ work in different systems to develop a systematic knowledge that can then inform and guide the construction of context-specific IQ models. This article analyzes the organization of IQ assurance work in a large-scale, open, collaborative encyclopedia - Wikipedia. What is special about Wikipedia as a resource is that the quality discussions and processes are strongly connected to the data itself and are accessible to the general public. This openness makes it particularly easy for researchers to study a particular kind of collaborative work that is highly distributed and that has a particularly substantial focus, not just on error detection but also on error correction. We believe that the study of those evolving debates and processes and of the IQ assurance model as a whole has useful implications for the improvement of quality in other more conventional databases.
    Type
    a
  4. Stvilia, B.; Mon, L.; Yi, Y.J.: ¬A model for online consumer health information quality (2009) 0.00 
    0.001757696 = product of:
  0.003515392 = sum of:
    0.003515392 = product of:
      0.007030784 = sum of:
        0.007030784 = weight(_text_:a in 3092) [ClassicSimilarity], result of:
          0.007030784 = score(doc=3092,freq=6.0), product of:
            0.053105544 = queryWeight, product of:
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.046056706 = queryNorm
            0.13239266 = fieldWeight in 3092, product of:
              2.4494898 = tf(freq=6.0), with freq of:
                6.0 = termFreq=6.0
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.046875 = fieldNorm(doc=3092)
      0.5 = coord(1/2)
  0.5 = coord(1/2)
    Abstract
    This article describes a model for online consumer health information consisting of five quality criteria constructs. These constructs are grounded in empirical data from the perspectives of the three main sources in the communication process: health information providers, consumers, and intermediaries, such as Web directory creators and librarians, who assist consumers in finding healthcare information. The article also defines five constructs of Web page structural markers that could be used in information quality evaluation and maps these markers to the quality criteria. Findings from correlation analysis and multinomial logistic tests indicate that use of the structural markers depended significantly on the type of Web page and type of information provider. The findings suggest the need to define genre-specific templates for quality evaluation and the need to develop models for an automatic genre-based classification of health information Web pages. In addition, the study showed that consumers may lack the motivation or literacy skills to evaluate the information quality of health Web pages, which suggests the need to develop accessible automatic information quality evaluation tools and ontologies.
    Type
    a

Authors

Themes