Search (12 results, page 1 of 1)

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Abstract

A citation index is a bibliographic database that provides citation links between documents. The first modern citation index was suggested by the researcher Eugene Garfield in 1955 and created by him in 1964, and it represents an important innovation to knowledge organization and information retrieval. This article describes citation indexes in general, considering the modern citation indexes, including Web of Science, Scopus, Google Scholar, Microsoft Academic, Crossref, Dimensions and some special citation indexes and predecessors to the modern citation index like Shepard's Citations. We present comparative studies of the major ones and survey theoretical problems related to the role of citation indexes as subject access points (SAP), recognizing the implications to knowledge organization and information retrieval. Finally, studies on citation behavior are presented and the influence of citation indexes on knowledge organization, information retrieval and the scientific information ecosystem is recognized.

Object

Science Citation Index

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Abstract

This article discusses definitions of index and indexing and provides a systematic overview of kinds of indexes. Theories of indexing are reviewed, and the theoretical basis of both manual indexing and automatic indexing is discussed, and a classification of theories is suggested (rationalist, cognitivist, empiricist, and historicist and pragmatist theories). It is claimed that although many researchers do not consider indexing to be a theoretical issue (or consider it to be a field without theories) indexing is indeed highly theory-laden (and the idea of atheoretical indexing is an oxymoron). An important issue is also the subjectivity of the indexer, in particular, her socio-cultural and paradigmatic background, as for example, when authors of documents are the best indexers of their own documents. The article contains a section about the tools available for indexing in the form of the indexing languages and their nature. It is concluded that the social epistemology first proposed by Jesse Shera in 1951 provides the most fruitful theoretical framework for indexing.

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Abstract

This article presents and discusses different kinds of data documents, including data sets, data studies, data papers and data journals. It provides descriptive and bibliometric data on different kinds of data documents and discusses the theoretical and philosophical problems by classifying documents according to the DIKW model (data documents, information documents, knowl­edge documents and wisdom documents). Data documents are, on the one hand, an established category today, even with its own data citation index (DCI). On the other hand, data documents have blurred boundaries in relation to other kinds of documents and seem sometimes to be understood from the problematic philosophical assumption that a datum can be understood as "a single, fixed truth, valid for everyone, everywhere, at all times".

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Abstract

This article discusses the different meanings of 'keyword' and related terms such as 'keyphrase', 'descriptor', 'index term', 'subject heading', 'tag' and 'n-gram' and suggests definitions of each of these terms. It further illustrates a classification of keywords, based on how they are produced or who is the actor generating them and present comparison between author-assigned keywords, indexer-assigned keywords and reader-assigned keywords as well as the automatic generation of keywords. The article also considers the functions of keywords including the use of keywords for generating bibliographic indexes. The theoretical view informing the article is that the assignment of a keyword to a text, picture or other document involves an interpretation of the document and an evaluation of the document's potentials for users. This perspective is important for both manually assigned keywords and for automated generation and is opposed to a strong tendency to consider a set of keywords as ideally presenting one best representation of a document for all requests.

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Date

21. 7.2006 14:11:22

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Pages

S.22-36

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Abstract

Special classifications have been somewhat neglected in KO compared to general classifications. The methodology of constructing special classifications is important, however, also for the methodology of constructing general classification schemes. The methodology of constructing special classifications can be regarded as one among about a dozen approaches to domain analysis. The methodology of (special) classification in LIS has been dominated by the rationalistic facet-analytic tradition, which, however, neglects the question of the empirical basis of classification. The empirical basis is much better grasped by, for example, bibliometric methods. Even the combination of rational and empirical methods is insufficient. This presentation will provide evidence for the necessity of historical and pragmatic methods for the methodology of classification and will point to the necessity of analyzing "paradigms". The presentation covers the methods of constructing classifications from Ranganathan to the design of ontologies in computer science and further to the recent "paradigm shift" in classification research. 1. Introduction Classification of a subject field is one among about eleven approaches to analyzing a domain that are specific for information science and in my opinion define the special competencies of information specialists (Hjoerland, 2002a). Classification and knowledge organization are commonly regarded as core qualifications of librarians and information specialists. Seen from this perspective one expects a firm methodological basis for the field. This paper tries to explore the state-of-the-art conceming the methodology of classification. 2. Classification: Science or non-science? As it is part of the curriculum at universities and subject in scientific journals and conferences like ISKO, orte expects classification/knowledge organization to be a scientific or scholarly activity and a scientific field. However, very often when information specialists classify or index documents and when they revise classification system, the methods seem to be rather ad hoc. Research libraries or scientific databases may employ people with adequate subject knowledge. When information scientists construct or evaluate systems, they very often elicit the knowledge from "experts" (Hjorland, 2002b, p. 260). Mostly no specific arguments are provided for the specific decisions in these processes.

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Date

17. 3.2011 19:22:55

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Date

22. 2.2013 11:49:13

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Source

Knowledge organization in the 21st century: between historical patterns and future prospects. Proceedings of the Thirteenth International ISKO Conference 19-22 May 2014, Kraków, Poland. Ed.: Wieslaw Babik

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Date

18.11.2023 13:47:22

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Date

22. 3.2009 18:13:27