Search (8 results, page 1 of 1)

0.023687614 = product of:
  0.09475046 = sum of:
    0.02538763 = weight(_text_:case in 1265) [ClassicSimilarity], result of:
      0.02538763 = score(doc=1265,freq=2.0), product of:
        0.1742197 = queryWeight, product of:
          4.3964143 = idf(docFreq=1480, maxDocs=44218)
          0.03962768 = queryNorm
        0.14572193 = fieldWeight in 1265, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          4.3964143 = idf(docFreq=1480, maxDocs=44218)
          0.0234375 = fieldNorm(doc=1265)
    0.06936283 = weight(_text_:studies in 1265) [ClassicSimilarity], result of:
      0.06936283 = score(doc=1265,freq=22.0), product of:
        0.15812531 = queryWeight, product of:
          3.9902744 = idf(docFreq=2222, maxDocs=44218)
          0.03962768 = queryNorm
        0.43865734 = fieldWeight in 1265, product of:
          4.690416 = tf(freq=22.0), with freq of:
            22.0 = termFreq=22.0
          3.9902744 = idf(docFreq=2222, maxDocs=44218)
          0.0234375 = fieldNorm(doc=1265)
  0.25 = coord(2/8)

Content

"In a new article published in Journal of Documentation, 2002, I claim that the special competency of information specialists and information scientists are related to "domain analysis." Information science grew out of special librarianship and documentation (cf. Williams, 1997), and implicit in its tradition has in my opinion been a focus an subject knowledge. Although domain analysis has earlier been introduced in JASIST (Hjoerland & Albrechtsen, 1995), the new article introduces 11 Specific approaches to domain analysis, which I Claim together define the Specific competencies of information specialists. The approaches are (I) Producing and evaluating literature guides and subject gateways, (2) Producing and evaluating special classifications and thesauri, (3) Research an and competencies in indexing and retrieving information specialties, (4) Knowledge about empirical user studies in subject areas, (5) Producing and interpreting bibliometrical studies, (6) Historical studies of information structures and Services in domains, (7) Studies of documents and genres in knowledge domains, (8) Epistemological and critical studies of different paradigms, assumptions, and interests in domains, (9) Knowledge about terminological studies, LSP (Languages for Special Purposes), and discourse analysis in knowledge fields, (10) Knowledge about and studies of structures and institutions in scientific and professional communication in a domain, (11) Knowledge about methods and results from domain analytic studies about professional cognition, knowledge representation in computer science and artificial intelligence. By bringing these approaches together, the paper advocates a view which may have been implicit in previous literature but which has not before been Set out systematically. The approaches presented here are neither exhaustive nor mutually exhaustve, but an attempt is made to present the state of the art. Specific examples and selective reviews of literature are provided, and the strength and drawback of each of these approaches are being discussed. It is my Claim that the information specialist who has worked with these 1 1 approaches in a given domain (e.g., music, sociology, or chemistry) has a special expertise that should not be mixed up with the kind of expertise taught at universities in corresponding subjects. Some of these 11 approaches are today well-known in schools of LIS. Bibliometrics is an example, Other approaches are new and represent a view of what should be introduced in the training of information professionals. First and foremost does the article advocates the view that these 1 1 approaches should be seen as supplementary. That the Professional identity is best maintained if Chose methods are applied to the same examples (same domain). Somebody would perhaps feel that this would make the education of information professionals too narrow. The Counter argument is that you can only understand and use these methods properly in a new domain, if you already have a deep knowledge of the Specific information problems in at least orte domain. It is a dangerous illusion to believe that one becomes more competent to work in any field if orte does not know anything about any domain. The special challenge in our science is to provide general background for use in Specific fields. This is what domain analysis is developed for. Study programs that allow the students to specialize and to work independent in the selected field (such as, for example, the Curriculum at the Royal School of LIS in Denmark) should fit well with the intentions in domain analysis. In this connection it should be emphasized that the 11 approaches are presented as general approaches that may be used in about any domain whatsoever. They should, however, be seen in connection. If this is not the case, then their relative strengths and weaknesses cannot be evaluated. The approaches do not have the same status. Some (e.g., empirical user studies) are dependent an others (e.g., epistemological studies).
It is my hope that domain analysis may contribute to the strengthening of the professional and scientific identity of our discipline and provide more coherence and depth in information studies. The paper is an argument about what should be core teachings in our field, It should be both broad enough to cover the important parts of IS and Specific enough to maintain a special focus and identity compared to, for example, computer science and the cognitive sciences. It is not a narrow view of information science and an the other hand it does not Set forth an unrealistic utopia."

0.008626453 = product of:
  0.06901162 = sum of:
    0.06901162 = weight(_text_:studies in 1118) [ClassicSimilarity], result of:
      0.06901162 = score(doc=1118,freq=4.0), product of:
        0.15812531 = queryWeight, product of:
          3.9902744 = idf(docFreq=2222, maxDocs=44218)
          0.03962768 = queryNorm
        0.43643627 = fieldWeight in 1118, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          3.9902744 = idf(docFreq=2222, maxDocs=44218)
          0.0546875 = fieldNorm(doc=1118)
  0.125 = coord(1/8)

Abstract

This article presents a brief history of the term "information" and its different meanings, which are both important and difficult because the different meanings of the term imply whole theories of knowledge. The article further considers the relation between "information" and the concepts "matter and energy", "data", "sign and meaning", "knowledge" and "communication". It presents and analyses the influence of information in information studies and knowledge organization and contains a presentation and critical analysis of some compound terms such as "information need", "information overload" and "information retrieval", which illuminate the use of the term information in information studies. An appendix provides a chronological list of definitions of information.

0.0052890894 = product of:
  0.042312715 = sum of:
    0.042312715 = weight(_text_:case in 3461) [ClassicSimilarity], result of:
      0.042312715 = score(doc=3461,freq=2.0), product of:
        0.1742197 = queryWeight, product of:
          4.3964143 = idf(docFreq=1480, maxDocs=44218)
          0.03962768 = queryNorm
        0.24286987 = fieldWeight in 3461, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          4.3964143 = idf(docFreq=1480, maxDocs=44218)
          0.0390625 = fieldNorm(doc=3461)
  0.125 = coord(1/8)

Abstract

Concept theory is an extremely broad, interdisciplinary and complex field of research related to many deep fields with very long historical traditions without much consensus. However, information science and knowledge organization cannot avoid relating to theories of concepts. Knowledge organizing systems (e.g., classification systems, thesauri, and ontologies) should be understood as systems basically organizing concepts and their semantic relations. The same is the case with information retrieval systems. Different theories of concepts have different implications for how to construe, evaluate, and use such systems. Based on a post-Kuhnian view of paradigms, this article put forward arguments that the best understanding and classification of theories of concepts is to view and classify them in accordance with epistemological theories (empiricism, rationalism, historicism, and pragmatism). It is also argued that the historicist and pragmatist understandings of concepts are the most fruitful views and that this understanding may be part of a broader paradigm shift that is also beginning to take place in information science. The importance of historicist and pragmatic theories of concepts for information science is outlined.

0.00522842 = product of:
  0.04182736 = sum of:
    0.04182736 = weight(_text_:studies in 304) [ClassicSimilarity], result of:
      0.04182736 = score(doc=304,freq=2.0), product of:
        0.15812531 = queryWeight, product of:
          3.9902744 = idf(docFreq=2222, maxDocs=44218)
          0.03962768 = queryNorm
        0.26452032 = fieldWeight in 304, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.9902744 = idf(docFreq=2222, maxDocs=44218)
          0.046875 = fieldNorm(doc=304)
  0.125 = coord(1/8)

Abstract

This article presents a socio-cognitive perspective in relation to information science (IS) and information retrieval (IR). The differences between traditional cognitive views and the socio-cognitive or domain-analytic view are outlined. It is claimed that, given elementary skills in computer-based retrieval, people are basically interacting with representations of subject literatures in IR. The kind of knowledge needed to interact with representations of subject literatures is discussed. It is shown how different approaches or "paradigms" in the represented literature imply different information needs and relevance criteria (which users typically cannot express very well, which is why IS cannot primarily rely on user studies). These principles are exemplified by comparing behaviorism, cognitivism, psychoanalysis, and neuroscience as approaches in psychology. The relevance criteria implicit in each position are outlined, and empirical data are provided to prove the theoretical claims. It is further shown that the most general level of relevance criteria is implied by epistemological theories. The article concludes that the fundamental problems of IS and IR are based in epistemology, which therefore becomes the most important allied field for IS.

0.005011469 = product of:
  0.040091753 = sum of:
    0.040091753 = weight(_text_:libraries in 6963) [ClassicSimilarity], result of:
      0.040091753 = score(doc=6963,freq=4.0), product of:
        0.13017908 = queryWeight, product of:
          3.2850544 = idf(docFreq=4499, maxDocs=44218)
          0.03962768 = queryNorm
        0.30797386 = fieldWeight in 6963, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          3.2850544 = idf(docFreq=4499, maxDocs=44218)
          0.046875 = fieldNorm(doc=6963)
  0.125 = coord(1/8)

Abstract

Information science has for a long time been drawing on the knowledge produced in psychology and related fields. This is reasonable, for the central issue in information science concerns individual users navigating information spaces such as libraries, databases, and the Internet, Thus, informations seeking is the fundamental problem in information science, while other problems, such as document representation, are subordinate. This book proposes a general theory of information seeking as a theoretical basis for information science

Footnote

Rez. in: nfd 49(1998) H.1, S.59-60 (G. Wersig), Erwiderung des Autors darauf in nfd: 49(1998) H.2, S.122-126; JASIS 49(1998) no.11, S.1043 (C. Chen); College and research libraries 59(1998) no.3, S.287-288 (P. Wilson)

0.004176224 = product of:
  0.033409793 = sum of:
    0.033409793 = weight(_text_:libraries in 832) [ClassicSimilarity], result of:
      0.033409793 = score(doc=832,freq=4.0), product of:
        0.13017908 = queryWeight, product of:
          3.2850544 = idf(docFreq=4499, maxDocs=44218)
          0.03962768 = queryNorm
        0.25664487 = fieldWeight in 832, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          3.2850544 = idf(docFreq=4499, maxDocs=44218)
          0.0390625 = fieldNorm(doc=832)
  0.125 = coord(1/8)

Abstract

The basic realist claim is that a mind-independent reality exists. It should be common sense knowledge to accept this claim, just as any theories that try to deny it soon become inconsistent because reality strikes back. In spite of this, antirealist philosophies flourish, not only in philosophy but also in the behavioral and cognitive sciences and in information science. This is highly problematic because it removes the attention from reality to subjective phenomena with no real explanatory power. Realism should not be confused with the view that all scientific claims are true or with any other kind of naiveté concerning knowledge claims. The opposite of realism may be termed antirealism, idealism, or nominalism. Although many people confuse empiricism and positivism with realism, these traditions are by nature strongly antirealist, which is why a sharp distinction should be made between empiricism and realism. Empirical research should not be founded on assumptions about "the given" of observations, but should recognize the theory-laden nature of observations. Domain analysis represents an attempt to reintroduce a realist perspective in library and information science. A realist conception of relevance, information seeking, information retrieval, and knowledge organization is outlined. Information systems of all kinds, including research libraries and public libraries, should be informed by a realist philosophy and a realist information science.

0.0031734537 = product of:
  0.02538763 = sum of:
    0.02538763 = weight(_text_:case in 5079) [ClassicSimilarity], result of:
      0.02538763 = score(doc=5079,freq=2.0), product of:
        0.1742197 = queryWeight, product of:
          4.3964143 = idf(docFreq=1480, maxDocs=44218)
          0.03962768 = queryNorm
        0.14572193 = fieldWeight in 5079, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          4.3964143 = idf(docFreq=1480, maxDocs=44218)
          0.0234375 = fieldNorm(doc=5079)
  0.125 = coord(1/8)

Abstract

The concept of information as we use it in everyday English, in the sense of knowledge communicated, plays a central role in contemporary society. The development and widespread use of computer networks since the end of World War II, and the emergence of information science as a discipline in the 1950s, are evidence of this focus. Although knowledge and its communication are basic phenomena of every human society, it is the rise of information technology and its global impacts that characterize ours as an information society. It is commonplace to consider information as a basic condition for economic development together with capital, labor, and raw material; but what makes information especially significant at present is its digital nature. The impact of information technology an the natural and social sciences in particular has made this everyday notion a highly controversial concept. Claude Shannon's (1948) "A Mathematical Theory of Communication" is a landmark work, referring to the common use of information with its semantic and pragmatic dimensions, while at the same time redefining the concept within an engineering framework. The fact that the concept of knowledge communication has been designated by the word information seems, prima facie, a linguistic happenstance. For a science like information science (IS), it is of course important how fundamental terms are defined; and in IS, as in other fields, the question of how to define information is often raised. This chapter is an attempt to review the status of the concept of information in IS, with reference also to interdisciplinary trends. In scientific discourse, theoretical concepts are not true or false elements or glimpses of some element of reality; rather, they are constructions designed to do a job in the best possible way. Different conceptions of fundamental terms like information are thus more or less fruitful, depending an the theories (and in the end, the practical actions) they are expected to support. In the opening section, we discuss the problem of defining terms from the perspective of the philosophy of science. The history of a word provides us with anecdotes that are tangential to the concept itself. But in our case, the use of the word information points to a specific perspective from which the concept of knowledge communication has been defined. This perspective includes such characteristics as novelty and relevante; i.e., it refers to the process of knowledge transformation, and particularly to selection and interpretation within a specific context. The discussion leads to the questions of why and when this meaning was designated with the word information. We will explore this history, and we believe that our results may help readers better understand the complexity of the concept with regard to its scientific definitions.

8.3890674E-4 = product of:
  0.006711254 = sum of:
    0.006711254 = product of:
      0.013422508 = sum of:
        0.013422508 = weight(_text_:22 in 2748) [ClassicSimilarity], result of:
          0.013422508 = score(doc=2748,freq=2.0), product of:
            0.13876937 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.03962768 = queryNorm
            0.09672529 = fieldWeight in 2748, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.01953125 = fieldNorm(doc=2748)
      0.5 = coord(1/2)
  0.125 = coord(1/8)

Date

22. 3.2009 18:13:27