Search (83 results, page 1 of 5)

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Abstract

A variety of schemas and ontologies are currently used for the machine-readable description of bibliographic entities and citations. This diversity, and the reuse of the same ontology terms with different nuances, generates inconsistencies in data. Adoption of a single data model would facilitate data integration tasks regardless of the data supplier or context application. In this paper we present the OpenCitations Data Model (OCDM), a generic data model for describing bibliographic entities and citations, developed using Semantic Web technologies. We also evaluate the effective reusability of OCDM according to ontology evaluation practices, mention existing users of OCDM, and discuss the use and impact of OCDM in the wider open science community.

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Abstract

Indexes in general seek to provide a "key" to a body of literature intending to help the user in identifying, verifying, and/or locating individual or related items. The most common devices for collocation in indexes are authors' names and subjects. A different approach to collocating related items in an index is provided by a method called "citation indexing." Citation indexes attempt to link items through citations or references, in other works, by bringing together items cited in a particular work and the works citing a particular item. Citation indexing is based an the concept that there is a significant intellectual link between a document and each bibliographic item cited in it and that this link is useful to the scholar because an author's references to earlier writings identify relevant information to the subject of his current work. One of the major differences between the citation index and the traditional subject index is that the former, while listing current literature, also provides a retrospec tive view of past literature. While each issue of a traditional index is normally concerned only with the current literature, the citation index brings back retrospective literature in the form of cited references, thereby linking current scholarly works with earlier works. The advantages of the citation index have been considered to be its value as a tool for tracing the history of ideas or discoveries, for associating ideas between current and past work, and for evaluating works of individual authors or library collections. The concept of citation indexing is not new. It has been applied to legal literature since 1873 in a legal reference tool called Shepard's Citations. In the 1950s Eugene Garfield, a documentation consultant and founder and President of the Institute for Scientific Information (Philadelphia), developed the technique of citation indexing for scientific literature. This new application was facilitated by the availability of computer technology, resulting in a series of services: Science Citation Index (1955- ), Social Sciences Citation Index (1966- ), and the Arts & Humanities Index (1976- ). All three appear in printed versions and as machine-readable databases. In the following essay, the first in a series of articles and books elucidating the citation indexing system, Garfield traces the origin and beginning of this idea, its advantages, and the methods of preparing such indexes.

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Abstract

Ahlgren, Jarneving, and. Rousseau review accepted procedures for author co-citation analysis first pointing out that since in the raw data matrix the row and column values are identical i,e, the co-citation count of two authors, there is no clear choice for diagonal values. They suggest the number of times an author has been co-cited with himself excluding self citation rather than the common treatment as zeros or as missing values. When the matrix is converted to a similarity matrix the normal procedure is to create a matrix of Pearson's r coefficients between data vectors. Ranking by r and by co-citation frequency and by intuition can easily yield three different orders. It would seem necessary that the adding of zeros to the matrix will not affect the value or the relative order of similarity measures but it is shown that this is not the case with Pearson's r. Using 913 bibliographic descriptions form the Web of Science of articles form JASIS and Scientometrics, authors names were extracted, edited and 12 information retrieval authors and 12 bibliometric authors each from the top 100 most cited were selected. Co-citation and r value (diagonal elements treated as missing) matrices were constructed, and then reconstructed in expanded form. Adding zeros can both change the r value and the ordering of the authors based upon that value. A chi-squared distance measure would not violate these requirements, nor would the cosine coefficient. It is also argued that co-citation data is ordinal data since there is no assurance of an absolute zero number of co-citations, and thus Pearson is not appropriate. The number of ties in co-citation data make the use of the Spearman rank order coefficient problematic.

Date

9. 7.2006 10:22:35

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Abstract

The Web of Science, an online database of bibliographic information produced by Thomson Reuters- draws its real value from the scholarly citation index at its core. By indexing the cited references from each paper as a separate part of the bibliographic data, a citation index creates a pathway by which a paper can be linked backward in time to the body of work that preceded it, as well as linked forward in time to its scholarly descendants. This entry provides a brief history of the development of the citation index, its core functionalities, and the way these unique data are provided to users through the Web of Science.

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Abstract

Vaughn, and Shaw look at the relationship between traditional citation and Web citation (not hyperlinks but rather textual mentions of published papers). Using English language research journals in ISI's 2000 Journal Citation Report - Information and Library Science category - 1209 full length papers published in 1997 in 46 journals were identified. Each was searched in Social Science Citation Index and on the Web using Google phrase search by entering the title in quotation marks, and followed for distinction where necessary with sub-titles, author's names, and journal title words. After removing obvious false drops, the number of web sites was recorded for comparison with the SSCI counts. A second sample from 1992 was also collected for examination. There were a total of 16,371 web citations to the selected papers. The top and bottom ranked four journals were then examined and every third citation to every third paper was selected and classified as to source type, domain, and country of origin. Web counts are much higher than ISI citation counts. Of the 46 journals from 1997, 26 demonstrated a significant correlation between Web and traditional citation counts, and 11 of the 15 in the 1992 sample also showed significant correlation. Journal impact factor in 1998 and 1999 correlated significantly with average Web citations per journal in the 1997 data, but at a low level. Thirty percent of web citations come from other papers posted on the web, and 30percent from listings of web based bibliographic services, while twelve percent come from class reading lists. High web citation journals often have web accessible tables of content.

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Abstract

We explore the intellectual subject structure and research themes in software engineering through the identification and analysis of a core journal literature. We examine this literature via two expert perspectives: that of the author, who identified significant work by citing it (journal cocitation analysis), and that of the professional indexer, who tags published work with subject terms to facilitate retrieval from a bibliographic database (subject profile analysis). The data sources are SCISEARCH (the on-line version of Science Citation Index), and INSPEC (a database covering software engineering, computer science, and information systems). We use data visualization tools (cluster analysis, multidimensional scaling, and PFNets) to show the "intellectual maps" of software engineering. Cocitation and subject profile analyses demonstrate that software engineering is a distinct interdisciplinary field, valuing practical and applied aspects, and spanning a subject continuum from "programming-in-the-smalI" to "programming-in-the-large." This continuum mirrors the software development life cycle by taking the operating system or major application from initial programming through project management, implementation, and maintenance. Object orientation is an integral but distinct subject area in software engineering. Key differences are the importance of management and programming: (1) cocitation analysis emphasizes project management and systems development; (2) programming techniques/languages are more influential in subject profiles; (3) cocitation profiles place object-oriented journals separately and centrally while the subject profile analysis locates these journals with the programming/languages group

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Abstract

The number and type of Web citations to journal articles in four areas of science are examined: biology, genetics, medicine, and multidisciplinary sciences. For a sample of 5,972 articles published in 114 journals, the median Web citation counts per journal article range from 6.2 in medicine to 10.4 in genetics. About 30% of Web citations in each area indicate intellectual impact (citations from articles or class readings, in contrast to citations from bibliographic services or the author's or journal's home page). Journals receiving more Web citations also have higher percentages of citations indicating intellectual impact. There is significant correlation between the number of citations reported in the databases from the Institute for Scientific Information (ISI, now Thomson Scientific) and the number of citations retrieved using the Google search engine (Web citations). The correlation is much weaker for journals published outside the United Kingdom or United States and for multidisciplinary journals. Web citation numbers are higher than ISI citation counts, suggesting that Web searches might be conducted for an earlier or a more fine-grained assessment of an article's impact. The Web-evident impact of non-UK/USA publications might provide a balance to the geographic or cultural biases observed in ISI's data, although the stability of Web citation counts is debatable.

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Abstract

References from publications are at the same time citations to other publications. This entry introduces some of the practical uses of citation data in science and scholarship. At the individual level citations identify and permit the retrieval of specific editions of works, while also suggesting their subject matter, authority, and age. Through citation indexes, retrievals may include not only the earlier items referred to by a given work, but also the later items that cite that given work in turn. Some technical notes on retrieval are included here. Counts of citations received over time, and measures derived from them, reveal the varying impacts of works, authors, journals, organizations, and countries. This has obvious implications for the evaluation of, e.g., library collections, academics, research teams, and science policies. When treated as linkages between pairs of publications, references and citations reveal intellectual ties. Several kinds of links have been defined, such as cocitation, bibliographic coupling, and intercitation. In the aggregate, these links form networks that compactly suggest the intellectual histories of research specialties and disciplines, especially when the networks are visualized through mapping software. Citation analysis is of course not without critics, who have long pointed out imperfections in the data or in analytical techniques. However, the criticisms have generally been met by strong counterarguments from proponents.

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Abstract

Historically, co-citation models have been based only on bibliographic information. Full-text analysis offers the opportunity to significantly improve the quality of the signals upon which these co-citation models are based. In this work we study the effect of reference proximity on the accuracy of co-citation clusters. Using a corpus of 270,521 full text documents from 2007, we compare the results of traditional co-citation clustering using only the bibliographic information to results from co-citation clustering where proximity between reference pairs is factored into the pairwise relationships. We find that accounting for reference proximity from full text can increase the textual coherence (a measure of accuracy) of a co-citation cluster solution by up to 30% over the traditional approach based on bibliographic information.

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Abstract

The reciprocal relationship between bibliographic references and citations in the context of the scholarly communication system is examined. Semiotic analysis of referencing behaviours and citation counting reveals the complexity of prevailing sign systems and associated symbolic practices.

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Abstract

Citation rates are becoming increasingly important in judging the research quality of journals, institutions and departments, and individual faculty. This paper looks at the pattern of citations across different management science journals and over time. A stochastic model is proposed which views the generating mechanism of citations as a gamma mixture of Poisson processes generating overall a negative binomial distribution. This is tested empirically with a large sample of papers published in 1990 from six management science journals and found to fit well. The model is extended to include obsolescence, i.e., that the citation rate for a paper varies over its cited lifetime. This leads to the additional citations distribution which shows that future citations are a linear function of past citations with a time-dependent and decreasing slope. This is also verified empirically in a way that allows different obsolescence functions to be fitted to the data. Conclusions concerning the predictability of future citations, and future research in this area are discussed.

Date

26.12.2007 19:22:05

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Abstract

Part 1 of a 2 part article reviewing the technique of bibliometrics and one of its most widely used methods, citation analysis. Traces the history and development of bibliometrics, including its definition, scope, role in scholarly communication and applications. Treats citation analysis similarly with particular reference to bibliographic coupling and cocitation coupling

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Date

13. 7.2008 19:53:22

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Date

7. 2.2005 14:10:22

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Abstract

We present an analysis of data citation practices based on the Data Citation Index (DCI) (Thomson Reuters). This database launched in 2012 links data sets and data studies with citations received from the other citation indexes. The DCI harvests citations to research data from papers indexed in the Web of Science. It relies on the information provided by the data repository. The findings of this study show that data citation practices are far from common in most research fields. Some differences have been reported on the way researchers cite data: Although in the areas of science and engineering & technology data sets were the most cited, in the social sciences and arts & humanities data studies play a greater role. A total of 88.1% of the records have received no citation, but some repositories show very low uncitedness rates. Although data citation practices are rare in most fields, they have expanded in disciplines such as crystallography and genomics. We conclude by emphasizing the role that the DCI could play in encouraging the consistent, standardized citation of research data-a role that would enhance their value as a means of following the research process from data collection to publication.

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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.

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Date

22. 7.2006 15:22:28

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Content

Inhalt: Biblio/sciento/infor-metrics : terminological issues and early historical developments -- The empirical foundations of bibliometrics : the Science citation index -- The philosophical foundations of bibliometrics : Bernal, Merton, Price, Garfield, and Small -- The mathematical foundations of bibliometrics -- Maps and paradigms : bibliographic citations at the service of the history and sociology of science -- Impact factor and the evaluation of scientists : bibliographic citations at the service of science policy and management -- On the shoulders of dwarfs : citation as rhetorical device and the criticisms to the normative model -- Measuring scientific communication in the twentieth century : from bibliometrics to cybermetrics.

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Abstract

Webometrics, the quantitative study of Web-related phenomena, emerged from the realization that methods originally designed for bibliometric analysis of scientific journal article citation patterns could be applied to the Web, with commercial search engines providing the raw data. Almind and Ingwersen (1997) defined the field and gave it its name. Other pioneers included Rodriguez Gairin (1997) and Aguillo (1998). Larson (1996) undertook exploratory link structure analysis, as did Rousseau (1997). Webometrics encompasses research from fields beyond information science such as communication studies, statistical physics, and computer science. In this review we concentrate on link analysis, but also cover other aspects of webometrics, including Web log fle analysis. One theme that runs through this chapter is the messiness of Web data and the need for data cleansing heuristics. The uncontrolled Web creates numerous problems in the interpretation of results, for instance, from the automatic creation or replication of links. The loose connection between top-level domain specifications (e.g., com, edu, and org) and their actual content is also a frustrating problem. For example, many .com sites contain noncommercial content, although com is ostensibly the main commercial top-level domain. Indeed, a skeptical researcher could claim that obstacles of this kind are so great that all Web analyses lack value. As will be seen, one response to this view, a view shared by critics of evaluative bibliometrics, is to demonstrate that Web data correlate significantly with some non-Web data in order to prove that the Web data are not wholly random. A practical response has been to develop increasingly sophisticated data cleansing techniques and multiple data analysis methods.