Search (48 results, page 1 of 3)

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Abstract

Why authors choose some references in preference to others is a question that is still not wholly answered despite its being of interest to scientists. The relevance of references is twofold: They are a mechanism for tracing the evolution of science, and because they enhance the image of the cited authors, citations are a widely known and used indicator of scientific endeavor. Following an extensive review of the literature, we selected all papers that seek to answer the central question and demonstrate that the existing theories are not sufficient: Neither citation nor indicator theory provides a complete and convincing answer. Some perspectives in this arena remain, which are isolated from the core literature. The purpose of this article is to offer a fresh perspective on a 30-year-old problem by extending the context of the discussion. We suggest reviving the discussion about citation theories with a new perspective, that of the readers, by layers or phases, in the final choice of references, allowing for a new classification in which any paper, to date, could be included.

Date

22. 3.2009 19:05:07

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Abstract

We propose an approach to visualizing the scientific world and its evolution by constructing minimum spanning trees (MSTs) and a two-dimensional map of scientific journals using the database of the Science Citation Index (SCI) during 1994-2001. The structures of constructed MSTs are consistent with the sorting of SCI categories. The map of science is constructed based on our MST results. Such a map shows the relation among various knowledge clusters and their citation properties. The temporal evolution of the scientific world can also be delineated in the map. In particular, this map clearly shows a linear structure of the scientific world, which contains three major domains including physical sciences, life sciences, and medical sciences. The interaction of various knowledge fields can be clearly seen from this scientific world map. This approach can be applied to various levels of knowledge domains.

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Abstract

The data systems, policies and procedures, corporate culture, and public face of an agency or institution make up its organizational interface. This case study describes how user interfaces for the Bureau of Labor Statistics web site evolved over a 5-year period along with the [arger organizational interface and how this co-evolution has influenced the institution itself. Interviews with BLS staff and transaction log analysis are the foci in this analysis that also included user informationseeking studies and user interface prototyping and testing. The results are organized into a model of organizational interface change and related to the information life cycle.

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Abstract

This article discusses the rationale for creating historiographs of scholarly topics using a new program called HistCite(TM), which produces a variety of analyses to aid the historian identify key events (papers), people (authors), and journals in a field. By creating a genealogic profile of the evolution, the program aids the scholar in evaluating the paradigm involved.

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Abstract

When there are a group of articles and the present time is fixed we can determine the unique number h being the number of articles that received h or more citations while the other articles received a number of citations which is not larger than h. In this article, the time dependence of the h-index is determined. This is important to describe the expected career evolution of a scientist's work or of a journal's production in a fixed year.

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Abstract

The universe of information has been enriched by the creation of the World Wide Web, which has become an indispensible source for research. Since this source is growing at an enormous speed, an in-depth look of its performance to create a method for its evaluation has become necessary; however, growth is not the only process that influences the evolution of the Web. During their lifetime, Web pages may change their content and links to/from other Web pages, be duplicated or moved to a different URL, be removed from the Web either temporarily or permanently, and be temporarily inaccessible due to server and/or communication failures. To obtain a better understanding of these processes, we developed a method for tracking topics on the Web for long periods of time, without the need to employ a crawler and relying only on publicly available resources. The multiple data-collection methods used allow us to discover new pages related to the topic, to identify changes to existing pages, and to detect previously existing pages that have been removed or whose content is not relevant anymore to the specified topic. The method is demonstrated through monitoring Web pages that contain the term informetrics for a period of 8 years. The data-collection method also allowed us to analyze the dynamic changes in search engine coverage, illustrated here on Google - the search engine used for the longest period of time for data collection in this project.

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Abstract

Like most activities in the world, scientific evolution has its own rhythm. How can this evolutionary rhythm be described and made visible? Do different fields have different rhythms, and how can they be measured? In order to answer these questions a relative indicator, called R-sequence, was designed. This indicator is time dependent, derived from publication and citation data, but independent of the absolute number of publications, as weIl as the absolute number of citations, and can therefore be used in a comparison of different scientific fields, nations, Institutes, or journals. Two caiculation methods of the R-sequence-the triangle method and the parallelogram method-are introduced. As a case study JASIS(T)'s R-sequence has been obtained.

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Abstract

One aim of science evaluation studies is to determine quantitatively the contribution of different players (authors, departments, countries) to the whole system. This information is then used to study the evolution of the system, for instance to gauge the results of special national or international programs. Taking articles as our basic data, we want to determine the exact relative contribution of each coauthor or each country. These numbers are brought together to obtain country scores, or department scores, etc. It turns out, as we will show in this article, that different scoring methods can yield totally different rankings. Conseqeuntly, a ranking between countries, universities, research groups or authors, based on one particular accrediting methods does not contain an absolute truth about their relative importance

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Abstract

According to the bibliographical data included in the Web of Science, SCOPUS, Chemical Abstracts, and other specialized information services covering the period 1900-1950, the first publications in mainstream journals by Mexican researchers appeared only in the first decades of the 20th century. Contrary to expectations, we find that the academic community was not the protagonist in the early stages of Mexican scientific practices, but that there was a strong contribution coming from researchers associated with the public-health sector and the chemical and mining industries. We were able to identify in this half century four different modes of scientific production: amateur, institutional, academic, and industrial, which in turn correspond to distinct stages in the evolution of the Mexican scientific production. We characterize these modes of production with a variety of indicators: publication and citation patterns, author output, journal and subject categories, institutional collaborations, and geographical distribution.

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Abstract

Webometrics is an information science field concerned with measuring aspects of the World Wide Web (WWW) for a variety of information science research goals. It came into existence about five years after the Web was formed and has since grown to become a significant aspect of information science, at least in terms of published research. Although some webometrics research has focused on the structure or evolution of the Web itself or the performance of commercial search engines, most has used data from the Web to shed light on information provision or online communication in various contexts. Most prominently, techniques have been developed to track, map, and assess Web-based informal scholarly communication, for example, in terms of the hyperlinks between academic Web sites or the online impact of digital repositories. In addition, a range of nonacademic issues and groups of Web users have also been analyzed.

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Abstract

We present evidence that in some research fields, research published in journals and reported on the Web may collectively represent different evolutionary stages of the field, with journals lagging a few years behind the Web on average, and that a "two-tier" scholarly communication system may therefore be evolving. We conclude that in such fields, (a) for detecting current research fronts, author co-citation analyses (ACA) using articles published on the Web as a data source can outperform traditional ACAs using articles published in journals as data, and that (b) as a result, it is important to use multiple data sources in citation analysis studies of scholarly communication for a complete picture of communication patterns. Our evidence stems from comparing the respective intellectual structures of the XML research field, a subfield of computer science, as revealed from three sets of ACA covering two time periods: (a) from the field's beginnings in 1996 to 2001, and (b) from 2001 to 2006. For the first time period, we analyze research articles both from journals as indexed by the Science Citation Index (SCI) and from the Web as indexed by CiteSeer. We follow up by an ACA of SCI data for the second time period. We find that most trends in the evolution of this field from the first to the second time period that we find when comparing ACA results from the SCI between the two time periods already were apparent in the ACA results from CiteSeer during the first time period.

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Abstract

Despite a very large number of studies on the aging and obsolescence of scientific literature, no study has yet measured, over a very long time period, the changes in the rates at which scientific literature becomes obsolete. This article studies the evolution of the aging phenomenon and, in particular, how the age of cited literature has changed over more than 100 years of scientific activity. It shows that the average and median ages of cited literature have undergone several changes over the period. Specifically, both World War I and World War II had the effect of significantly increasing the age of the cited literature. The major finding of this article is that contrary to a widely held belief, the age of cited material has risen continuously since the mid-1960s. In other words, during that period, researchers were relying on an increasingly old body of literature. Our data suggest that this phenomenon is a direct response to the steady-state dynamics of modern science that followed its exponential growth; however, we also have observed that online preprint archives such as arXiv have had the opposite effect in some subfields.

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Abstract

We use a technique recently developed by V. Blondel, J.-L. Guillaume, R. Lambiotte, and E. Lefebvre (2008) to detect scientific specialties from author cocitation networks. This algorithm has distinct advantages over most previous methods used to obtain cocitation clusters since it avoids the use of similarity measures, relies entirely on the topology of the weighted network, and can be applied to relatively large networks. Most importantly, it requires no subjective interpretation of the cocitation data or of the communities found. Using two examples, we show that the resulting specialties are the smallest coherent groups of researchers (within a hierarchy of cluster sizes) and can thus be identified unambiguously. Furthermore, we confirm that these communities are indeed representative of what we know about the structure of a given scientific discipline and that as specialties, they can be accurately characterized by a few keywords (from the publication titles). We argue that this robust and efficient algorithm is particularly well-suited to cocitation networks and that the results generated can be of great use to researchers studying various facets of the structure and evolution of science.

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Abstract

Die Szientometrie beschäftigt sich mit der Messbarkeit wissenschaftlicher Leistungen anhand bibliothekarisch nachweisbarer Publikationsergebnisse. Bei genauer Betrachtung ist es ihr Ziel, die Wissenszunahme der Wissenschaft zu messen. Die wissenschaftliche Produktion in Form von Publikationen wächst seit über dreihundert Jahren konstant mit ca. 3,5% pro Jahr. Das entspricht einerVerdopplungsrate von 20 Jahren, die zuerst dem Bibliothekar Fremont Rider 1948 bei Büchern auffiel und die 1963 von Derek J. de Solla Price auch für das Wachstum von Zeitschriften und Bibliografien bestätigt wurde. Die Konstanz dieser Evolution, unabhängig aller sich ereignenden Katastrophen, ist nur zum Teil verstanden, macht aber den unaufhaltsamen Fortschritt der Wissenschaft deutlich. Alle 20 Jahre wird so viel publiziert wie in allen Jahrhunderten davor. Eine etwa gleiche Zunahme verzeichnen die Wissenschaftler, die damit etwa gleich produktiv bleiben. Von ihnen allen sind damit ca. 87% unsere heutigen Zeitgenossen. Aus diesem Wachstum heraus können wir abschätzen, dass in 100.000 laufenden Zeitschriften heute etwa 10 Mio. Publikationen jährlich erscheinen, die von 10 Mio. Wissenschaftlern verfasst werden. Dabei definieren sich nur die als Wissenschaftler, die durchschnittlich eine Publikation jährlich verfassen. Die gesamte Produktion an Buchtiteln, die bisher erschien, dürfte bei etwa 100 Mio. liegen. Davon sind etwa 20 Mio. als wissenschaftlich einzustufen. Wenn folglich 87% aller Wissenschaftler noch heute leben, so betrug die Gesamtzahl der Wissenschaftler in der Welt bisher 11,5 Mio., die in ihrem Leben durchschnittlich 1,5 Bücher pro Kopf verfassten, und etwa das 10-20fache an Zeitschriftenbeiträgen leisteten. Ein Teil dieser Bücher sind allerdings Neuauflagen und Übersetzungen. Nach Lotka, A. J. ist die Produktivität der Wissenschaftler eine schiefe Verteilung von der Form A/n**2, wobei A die Zahl der Autoren mit nur einer Publikation ist und n die Publikationen pro Autor. Während Price in seinen "Networks of Scientific Papers" Vergleichswerte von n**2,5 bis n**3 angab, zeigten Untersuchungen am Science Citation Index (SCI), die auf die gesamte naturwissenschaftliche Literatur hochgerechnet wurden, eher einen Wert von n**1,7. Auf die Tatsache, dass eine Verdopplungsrate der Wissenschaftler von 20 Jahren und eine solche der Menschheit von etwa 50 Jahren dazu führt, dass eines Tages alle Menschen Wissenschaftler werden, hat Price bereits 1963 hingewiesen. Dieser Zustand müsste bei 10 Mio. Wissenschaftlern und 6 Mrd. Menschen in etwa 300 Jahren eintreten, ein nur scheinbar absurder Gedanke, wenn man bedenkt, dass man sich vor 300 Jahren auch kaum vorstellen konnte, dass alle Menschen Lesen, Schreiben und Rechnen lernen können, und dass wir uns ungebildete Menschen immer weniger leisten können.

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Date

13. 7.2008 19:53:22

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Date

22. 7.2006 15:22:28

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Date

20. 1.2007 17:02:22