Search (7 results, page 1 of 1)

0.049779683 = product of:
  0.09955937 = sum of:
    0.068930924 = weight(_text_:digital in 3738) [ClassicSimilarity], result of:
      0.068930924 = score(doc=3738,freq=2.0), product of:
        0.19770671 = queryWeight, product of:
          3.944552 = idf(docFreq=2326, maxDocs=44218)
          0.050121464 = queryNorm
        0.34865242 = fieldWeight in 3738, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.944552 = idf(docFreq=2326, maxDocs=44218)
          0.0625 = fieldNorm(doc=3738)
    0.030628446 = weight(_text_:library in 3738) [ClassicSimilarity], result of:
      0.030628446 = score(doc=3738,freq=2.0), product of:
        0.1317883 = queryWeight, product of:
          2.6293786 = idf(docFreq=8668, maxDocs=44218)
          0.050121464 = queryNorm
        0.23240642 = fieldWeight in 3738, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          2.6293786 = idf(docFreq=8668, maxDocs=44218)
          0.0625 = fieldNorm(doc=3738)
  0.5 = coord(2/4)

Content

Digital unter: http://dx.doi.org/10.1081/E-ELIS3-120043711. Vgl.: http://www.tandfonline.com/doi/book/10.1081/E-ELIS3.

Source

Encyclopedia of library and information sciences. 3rd ed. Ed.: M.J. Bates

0.043557227 = product of:
  0.08711445 = sum of:
    0.060314562 = weight(_text_:digital in 2715) [ClassicSimilarity], result of:
      0.060314562 = score(doc=2715,freq=2.0), product of:
        0.19770671 = queryWeight, product of:
          3.944552 = idf(docFreq=2326, maxDocs=44218)
          0.050121464 = queryNorm
        0.30507088 = fieldWeight in 2715, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.944552 = idf(docFreq=2326, maxDocs=44218)
          0.0546875 = fieldNorm(doc=2715)
    0.026799891 = weight(_text_:library in 2715) [ClassicSimilarity], result of:
      0.026799891 = score(doc=2715,freq=2.0), product of:
        0.1317883 = queryWeight, product of:
          2.6293786 = idf(docFreq=8668, maxDocs=44218)
          0.050121464 = queryNorm
        0.20335563 = fieldWeight in 2715, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          2.6293786 = idf(docFreq=8668, maxDocs=44218)
          0.0546875 = fieldNorm(doc=2715)
  0.5 = coord(2/4)

Abstract

The knowledge represented in learning materials for the sciences is typically organized around term-based or "weakly-structured" models of concepts and their interrelationships. We introduce a "strongly-structured" model of scientific concepts that provides the foundation for a knowledge base (KB) of concept representations. An extension of the Alexandria Digital Library employs such a KB, together with associated collection and services, to support undergraduate leaming.

0.042796366 = product of:
  0.08559273 = sum of:
    0.060926907 = weight(_text_:digital in 1176) [ClassicSimilarity], result of:
      0.060926907 = score(doc=1176,freq=4.0), product of:
        0.19770671 = queryWeight, product of:
          3.944552 = idf(docFreq=2326, maxDocs=44218)
          0.050121464 = queryNorm
        0.3081681 = fieldWeight in 1176, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          3.944552 = idf(docFreq=2326, maxDocs=44218)
          0.0390625 = fieldNorm(doc=1176)
    0.024665821 = product of:
      0.049331643 = sum of:
        0.049331643 = weight(_text_:project in 1176) [ClassicSimilarity], result of:
          0.049331643 = score(doc=1176,freq=2.0), product of:
            0.21156175 = queryWeight, product of:
              4.220981 = idf(docFreq=1764, maxDocs=44218)
              0.050121464 = queryNorm
            0.23317845 = fieldWeight in 1176, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              4.220981 = idf(docFreq=1764, maxDocs=44218)
              0.0390625 = fieldNorm(doc=1176)
      0.5 = coord(1/2)
  0.5 = coord(2/4)

Abstract

The rapid growth of Internet resources and digital collections has been accompanied by a proliferation of metadata schemas, each of which has been designed based on the requirements of particular user communities, intended users, types of materials, subject domains, project needs, etc. Problems arise when building large digital libraries or repositories with metadata records that were prepared according to diverse schemas. This article (published in two parts) contains an analysis of the methods that have been used to achieve or improve interoperability among metadata schemas and applications, for the purposes of facilitating conversion and exchange of metadata and enabling cross-domain metadata harvesting and federated searches. From a methodological point of view, implementing interoperability may be considered at different levels of operation: schema level, record level, and repository level. Part I of the article intends to explain possible situations in which metadata schemas may be created or implemented, whether in individual projects or in integrated repositories. It also discusses approaches used at the schema level. Part II of the article will discuss metadata interoperability efforts at the record and repository levels.

0.021324418 = product of:
  0.085297674 = sum of:
    0.085297674 = weight(_text_:digital in 2620) [ClassicSimilarity], result of:
      0.085297674 = score(doc=2620,freq=4.0), product of:
        0.19770671 = queryWeight, product of:
          3.944552 = idf(docFreq=2326, maxDocs=44218)
          0.050121464 = queryNorm
        0.43143538 = fieldWeight in 2620, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          3.944552 = idf(docFreq=2326, maxDocs=44218)
          0.0546875 = fieldNorm(doc=2620)
  0.25 = coord(1/4)

Abstract

Describes the use of concept maps as one of the semantic tools employed in the ADEPT (Alexandria Digital Earth Prototype) Digital Learning Environment (DLE) for teaching undergraduate classes. The graphic representation of the conceptualizations is derived from the knowledge in stronglystructured models (SSMs) of concepts represented in one or more knowledge bases. Such knowledge bases function as a source of "reference" information about concepts in a given context, including information about their scientific representation, scientific semantics, manipulation, and interrelationships to other concepts.

0.020432387 = product of:
  0.040864773 = sum of:
    0.021657582 = weight(_text_:library in 2654) [ClassicSimilarity], result of:
      0.021657582 = score(doc=2654,freq=4.0), product of:
        0.1317883 = queryWeight, product of:
          2.6293786 = idf(docFreq=8668, maxDocs=44218)
          0.050121464 = queryNorm
        0.16433616 = fieldWeight in 2654, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          2.6293786 = idf(docFreq=8668, maxDocs=44218)
          0.03125 = fieldNorm(doc=2654)
    0.019207189 = product of:
      0.038414378 = sum of:
        0.038414378 = weight(_text_:22 in 2654) [ClassicSimilarity], result of:
          0.038414378 = score(doc=2654,freq=4.0), product of:
            0.17551683 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.050121464 = queryNorm
            0.21886435 = fieldWeight in 2654, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.03125 = fieldNorm(doc=2654)
      0.5 = coord(1/2)
  0.5 = coord(2/4)

Abstract

In order to transfer the Chinese Classified Thesaurus (CCT) into a machine-processable format and provide CCT-based Web services, a pilot study has been conducted in which a variety of selected CCT classes and mapped thesaurus entries are encoded with SKOS. OWL and RDFS are also used to encode the same contents for the purposes of feasibility and cost-benefit comparison. CCT is a collected effort led by the National Library of China. It is an integration of the national standards Chinese Library Classification (CLC) 4th edition and Chinese Thesaurus (CT). As a manually created mapping product, CCT provides for each of the classes the corresponding thesaurus terms, and vice versa. The coverage of CCT includes four major clusters: philosophy, social sciences and humanities, natural sciences and technologies, and general works. There are 22 main-classes, 52,992 sub-classes and divisions, 110,837 preferred thesaurus terms, 35,690 entry terms (non-preferred terms), and 59,738 pre-coordinated headings (Chinese Classified Thesaurus, 2005) Major challenges of encoding this large vocabulary comes from its integrated structure. CCT is a result of the combination of two structures (illustrated in Figure 1): a thesaurus that uses ISO-2788 standardized structure and a classification scheme that is basically enumerative, but provides some flexibility for several kinds of synthetic mechanisms Other challenges include the complex relationships caused by differences of granularities of two original schemes and their presentation with various levels of SKOS elements; as well as the diverse coordination of entries due to the use of auxiliary tables and pre-coordinated headings derived from combining classes, subdivisions, and thesaurus terms, which do not correspond to existing unique identifiers. The poster reports the progress, shares the sample SKOS entries, and summarizes problems identified during the SKOS encoding process. Although OWL Lite and OWL Full provide richer expressiveness, the cost-benefit issues and the final purposes of encoding CCT raise questions of using such approaches.

Source

Metadata for semantic and social applications : proceedings of the International Conference on Dublin Core and Metadata Applications, Berlin, 22 - 26 September 2008, DC 2008: Berlin, Germany / ed. by Jane Greenberg and Wolfgang Klas

0.0061664553 = product of:
  0.024665821 = sum of:
    0.024665821 = product of:
      0.049331643 = sum of:
        0.049331643 = weight(_text_:project in 6740) [ClassicSimilarity], result of:
          0.049331643 = score(doc=6740,freq=2.0), product of:
            0.21156175 = queryWeight, product of:
              4.220981 = idf(docFreq=1764, maxDocs=44218)
              0.050121464 = queryNorm
            0.23317845 = fieldWeight in 6740, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              4.220981 = idf(docFreq=1764, maxDocs=44218)
              0.0390625 = fieldNorm(doc=6740)
      0.5 = coord(1/2)
  0.25 = coord(1/4)

Abstract

A problem facing information retrieval and exchange among international medical practitioners and researchers is the lack of a knowledge structure or conceptual framework that relates concepts used in the Western medical system to those used in non-Western medical systems. This paper presents challenges we have encountered in attempting to develop a general conceptual framework to cover concepts and terminology used for information retrieval in the field of complementary and alternative medicine. This is a broad field that has not been covered appropriately in knowledge organization systems such as classification schemes, thesauri, and terminology databases. The objective of the project is to improve significantly the efficiency and the quality of cross-language and cross-cultural information exchange and knowledge discovery by facilitating concept mapping and information retrieval between Western and Eastern medical traditions. Major facets of the conceptual framework include Diagnostic Categories, Therapeutic Preparations, Human Anatomy, Selected Diseases/Medical Conditions, and Basics of Traditional Systems. The paper discusses issues of subject coverage, the representation of medical concepts in the conceptual framework, incorporation of concept names that have existed in individual traditional systems, and the relationships among concepts. Findings reported are primarily from current work that focuses on Traditional Chinese Medicine.

0.0049331645 = product of:
  0.019732658 = sum of:
    0.019732658 = product of:
      0.039465316 = sum of:
        0.039465316 = weight(_text_:project in 1177) [ClassicSimilarity], result of:
          0.039465316 = score(doc=1177,freq=2.0), product of:
            0.21156175 = queryWeight, product of:
              4.220981 = idf(docFreq=1764, maxDocs=44218)
              0.050121464 = queryNorm
            0.18654276 = fieldWeight in 1177, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              4.220981 = idf(docFreq=1764, maxDocs=44218)
              0.03125 = fieldNorm(doc=1177)
      0.5 = coord(1/2)
  0.25 = coord(1/4)

Abstract

This is the second part of an analysis of the methods that have been used to achieve or improve interoperability among metadata schemas and their applications in order to facilitate the conversion and exchange of metadata and to enable cross-domain metadata harvesting and federated searches. From a methodological point of view, implementing interoperability may be considered at different levels of operation: schema level (discussed in Part I of the article), record level (discussed in Part II of the article), and repository level (also discussed in Part II). The results of efforts to improve interoperability may be observed from different perspectives as well, including element-based and value-based approaches. As discussed in Part I of this study, the results of efforts to improve interoperability can be observed at different levels: 1. Schema level - Efforts are focused on the elements of the schemas, being independent of any applications. The results usually appear as derived element sets or encoded schemas, crosswalks, application profiles, and element registries. 2. Record level - Efforts are intended to integrate the metadata records through the mapping of the elements according to the semantic meanings of these elements. Common results include converted records and new records resulting from combining values of existing records. 3. Repository level - With harvested or integrated records from varying sources, efforts at this level focus on mapping value strings associated with particular elements (e.g., terms associated with subject or format elements). The results enable cross-collection searching. In the following sections, we will continue to analyze interoperability efforts and methodologies, focusing on the record level and the repository level. It should be noted that the models to be discussed in this article are not always mutually exclusive. Sometimes, within a particular project, more than one method may be used.