Search (3 results, page 1 of 1)

0.004527677 = product of:
  0.022638384 = sum of:
    0.022638384 = product of:
      0.04527677 = sum of:
        0.04527677 = weight(_text_:management in 3379) [ClassicSimilarity], result of:
          0.04527677 = score(doc=3379,freq=4.0), product of:
            0.14328322 = queryWeight, product of:
              3.3706124 = idf(docFreq=4130, maxDocs=44218)
              0.042509552 = queryNorm
            0.31599492 = fieldWeight in 3379, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              3.3706124 = idf(docFreq=4130, maxDocs=44218)
              0.046875 = fieldNorm(doc=3379)
      0.5 = coord(1/2)
  0.2 = coord(1/5)

Abstract

The main motivation of this chapter was to gather existing requirements and solutions, and to present a generic architectural design of semantic digital libraries. This design is meant to answer a number of requirements, such as interoperability or ability to exchange resources and solutions, and set up the foundations for the best practices in the new domain of semantic digital libraries. We start by presenting the library from different high-level perspectives, i.e., user (see Sect. 2) and metadata (see Sect. 1) perspective; this overview narrows the scope and puts emphasis on certain aspects related to the system perspective, i.e., the architecture of the actual digital library management system. We conclude by presenting the system architecture from three perspectives: top-down layered architecture (see Sect. 3), vertical architecture of core services (see Sect. 4), and stack of enabling infrastructures (see Sect. 5); based upon the observations and evaluation of the contemporary state of the art presented in the previous sections, these last three subsections will describe an in-depth model of the digital library management system.

0.002667959 = product of:
  0.013339795 = sum of:
    0.013339795 = product of:
      0.02667959 = sum of:
        0.02667959 = weight(_text_:management in 672) [ClassicSimilarity], result of:
          0.02667959 = score(doc=672,freq=2.0), product of:
            0.14328322 = queryWeight, product of:
              3.3706124 = idf(docFreq=4130, maxDocs=44218)
              0.042509552 = queryNorm
            0.18620178 = fieldWeight in 672, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.3706124 = idf(docFreq=4130, maxDocs=44218)
              0.0390625 = fieldNorm(doc=672)
      0.5 = coord(1/2)
  0.2 = coord(1/5)

Abstract

This chapter describes not so much what digital libraries are but what digital libraries with semantic support could and should be. It discusses the nature of Knowledge Organization Systems (KOS) and how KOS can support digital library users. It projects a vision for designers to make and for users to demand better digital libraries. What is a digital library? The term \Digital Library" (DL) is used to refer to a range of systems, from digital object and metadata repositories, reference-linking systems, archives, and content management systems to complex systems that integrate advanced digital library services and support for research and practice communities. A DL may offer many technology-enabled functions and services that support users, both as information producers and as information users. Many of these functions appear in information systems that would not normally be considered digital libraries, making boundaries even more blurry. Instead of pursuing the hopeless quest of coming up with the definition of digital library, we present a framework that allows a clear and somewhat standardized description of any information system so that users can select the system(s) that best meet their requirements. Section 2 gives a broad outline for more detail see the DELOS DL Reference Model.

0.0021343674 = product of:
  0.010671836 = sum of:
    0.010671836 = product of:
      0.021343673 = sum of:
        0.021343673 = weight(_text_:management in 2799) [ClassicSimilarity], result of:
          0.021343673 = score(doc=2799,freq=2.0), product of:
            0.14328322 = queryWeight, product of:
              3.3706124 = idf(docFreq=4130, maxDocs=44218)
              0.042509552 = queryNorm
            0.14896142 = fieldWeight in 2799, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.3706124 = idf(docFreq=4130, maxDocs=44218)
              0.03125 = fieldNorm(doc=2799)
      0.5 = coord(1/2)
  0.2 = coord(1/5)

Abstract

Grounded on a strong belief that ontologies enhance the performance of information retrieval systems, there has been an upsurge of interest in ontologies. Its importance is identified in diverse research fields such as knowledge engineering, knowledge representation, qualitative modeling, language engineering, database design, information integration, object-oriented analysis, information retrieval and extraction, knowledge management and agent-based systems design (Guarino, 1998). While the role-played by ontologies, automatically lends a place of legitimacy for these tools, research in this area gains greater significance in the wake of various challenges faced in the contemporary digital environment. With the objective of overcoming various pitfalls associated with current search mechanisms, ontologies are increasingly used for developing efficient information retrieval systems. An indicator of research interest in the area of ontology is the Swoogle, a search engine for Semantic Web documents, terms and data found on the Web (Ding, Li et al, 2004). Given the complex nature of the digital content archived in digital libraries, ontologies can be employed for designing efficient forms of information retrieval in digital libraries. Knowledge representation assumes greater significance due to its crucial role in ontology development. These systems aid in developing intelligent information systems, wherein the notion of intelligence implies the ability of the system to find implicit consequences of its explicitly represented knowledge (Baader and Nutt, 2003). Knowledge representation formalisms such as 'Description Logics' are used to obtain explicit knowledge representation of the subject domain. These representations are developed into ontologies, which are used for developing intelligent information systems. Against this backdrop, the paper examines the use of Description Logics for conceptually modeling a chosen domain, which would be utilized for developing domain ontologies. The knowledge representation languages identified for this purpose are Web Ontology Language (OWL) and KArlsruhe ONtology (KAON) language. Drawing upon the various technical constructs in developing ontology-based information systems, the paper explains the working of the prototypes and also presents a comparative study of the two prototypes.