Search (21 results, page 1 of 2)

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Date

22. 7.2006 15:22:28

Type

a

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Abstract

The h-index has been shown to increase in many cases mostly because of citations to rather old publications. This inertia can be circumvented by restricting the evaluation to a citation time window. Here I report results of an empirical study analyzing the evolution of the thus defined timed h-index in dependence on the length of the citation time window.

Type

a

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Abstract

Publication in academic journals is a key criterion for appointment, tenure and promotion in universities. Many universities weigh publications according to the quality or impact of the journal. Traditionally, journal quality has been assessed through the ISI Journal Impact Factor (JIF). This paper proposes an alternative metric - Hirsch's h-index - and data source - Google Scholar - to assess journal impact. Using a systematic comparison between the Google Scholar h-index and the ISI JIF for a sample of 838 journals in Economics & Business, we argue that the former provides a more accurate and comprehensive measure of journal impact.

Type

a

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Abstract

Increasingly researchers and academic research institutions are being asked to demonstrate the quality and impact of their research. Traditionally researchers have used text-based outputs to achieve these objectives. This paper discusses the introduction and subsequent review of a new service at a major Australian university, designed to encourage researchers to use media, particularly visual formats, in promoting their research. Findings from the review have highlighted the importance of researchers working in partnership with in-house media professionals to produce short, relatable, digestible, and engaging visual products. As a result of these findings, the authors have presented a four-phase media development model to assist researchers to tell their research story. The paper concludes with a discussion of the implications for the institution as a whole and, more specifically, libraries.

Type

a

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Abstract

Following a recent idea, to measure fame by the number of \Google hits found in a search on the WWW, we study the relation between fame (\Google hits) and merit (number of papers posted on an electronic archive) for a random group of scientists in condensed matter and statistical physics. Our findings show that fame and merit in science are linearly related, and that the probability distribution for a certain level of fame falls off exponentially. This is in sharp contrast with the original findings about WW II ace pilots, for which fame is exponentially related to merit (number of downed planes), and the probability of fame decays in power-law fashion. Other groups in our study show similar patterns of fame as for ace pilots.

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Abstract

This is a report about the use and misuse of citation data in the assessment of scientific research. The idea that research assessment must be done using "simple and objective" methods is increasingly prevalent today. The "simple and objective" methods are broadly interpreted as bibliometrics, that is, citation data and the statistics derived from them. There is a belief that citation statistics are inherently more accurate because they substitute simple numbers for complex judgments, and hence overcome the possible subjectivity of peer review. But this belief is unfounded. - Relying on statistics is not more accurate when the statistics are improperly used. Indeed, statistics can mislead when they are misapplied or misunderstood. Much of modern bibliometrics seems to rely on experience and intuition about the interpretation and validity of citation statistics. - While numbers appear to be "objective", their objectivity can be illusory. The meaning of a citation can be even more subjective than peer review. Because this subjectivity is less obvious for citations, those who use citation data are less likely to understand their limitations. - The sole reliance on citation data provides at best an incomplete and often shallow understanding of research - an understanding that is valid only when reinforced by other judgments. Numbers are not inherently superior to sound judgments.
Using citation data to assess research ultimately means using citation-based statistics to rank things.journals, papers, people, programs, and disciplines. The statistical tools used to rank these things are often misunderstood and misused. - For journals, the impact factor is most often used for ranking. This is a simple average derived from the distribution of citations for a collection of articles in the journal. The average captures only a small amount of information about that distribution, and it is a rather crude statistic. In addition, there are many confounding factors when judging journals by citations, and any comparison of journals requires caution when using impact factors. Using the impact factor alone to judge a journal is like using weight alone to judge a person's health. - For papers, instead of relying on the actual count of citations to compare individual papers, people frequently substitute the impact factor of the journals in which the papers appear. They believe that higher impact factors must mean higher citation counts. But this is often not the case! This is a pervasive misuse of statistics that needs to be challenged whenever and wherever it occurs. -For individual scientists, complete citation records can be difficult to compare. As a consequence, there have been attempts to find simple statistics that capture the full complexity of a scientist's citation record with a single number. The most notable of these is the h-index, which seems to be gaining in popularity. But even a casual inspection of the h-index and its variants shows that these are naive attempts to understand complicated citation records. While they capture a small amount of information about the distribution of a scientist's citations, they lose crucial information that is essential for the assessment of research.
The validity of statistics such as the impact factor and h-index is neither well understood nor well studied. The connection of these statistics with research quality is sometimes established on the basis of "experience." The justification for relying on them is that they are "readily available." The few studies of these statistics that were done focused narrowly on showing a correlation with some other measure of quality rather than on determining how one can best derive useful information from citation data. We do not dismiss citation statistics as a tool for assessing the quality of research.citation data and statistics can provide some valuable information. We recognize that assessment must be practical, and for this reason easily-derived citation statistics almost surely will be part of the process. But citation data provide only a limited and incomplete view of research quality, and the statistics derived from citation data are sometimes poorly understood and misused. Research is too important to measure its value with only a single coarse tool. We hope those involved in assessment will read both the commentary and the details of this report in order to understand not only the limitations of citation statistics but also how better to use them. If we set high standards for the conduct of science, surely we should set equally high standards for assessing its quality.

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Abstract

The use of research impact metrics and analytics has become an integral component to many aspects of institutional assessment. Many platforms currently exist to provide such analytics, both proprietary and open source; however, the functionality of these systems may not always overlap to serve uniquely specific needs. In this paper, I describe a novel web-based platform, named Manifold, that I built to serve custom research impact assessment needs in the University of Minnesota Medical School. Built on a standard LAMP architecture, Manifold automatically pulls publication data for faculty from Scopus through APIs, calculates impact metrics through automated analytics, and dynamically generates report-like profiles that visualize those metrics. Work on this project has resulted in many lessons learned about challenges to sustainability and scalability in developing a system of such magnitude.

Type

a

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Abstract

The scientific community's growing eagerness to make research data available to the public provides libraries - with our expertise in metadata and discovery - an interesting new opportunity. This paper details the in-house creation of a "data catalog" which describes datasets ranging from population-level studies like the US Census to small, specialized datasets created by researchers at our own institution. Based on Symfony2 and Solr, the data catalog provides a powerful search interface to help researchers locate the data that can help them, and an administrative interface so librarians can add, edit, and manage metadata elements at will. This paper will outline the successes, failures, and total redos that culminated in the current manifestation of our data catalog.

Type

a

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Abstract

If you are an academic researcher but did not earn (yet) your Nobel prize or your retirement, it is unlikely you never heard about research metrics. These metrics aim at quantifying various aspects of the research process, at the level of individual researchers (e.g. h-index, altmetrics), scientific journals (e.g. impact factors) or entire universities/ countries (e.g. rankings). Although such "measurements" have existed in a simple form for a long time, their widespread calculation was enabled by the advent of the digital era (large amount of data available worldwide in a computer-compatible format). And in this new era, what becomes technically possible will be done, and what is done and appears to simplify our lives will be used. As a result, a rapidly growing number of statistics-based numerical indices are nowadays fed into decisionmaking processes. This is true in nearly all aspects of society (politics, economy, education and private life), and in particular in research, where metrics play an increasingly important role in determining positions, funding, awards, research programs, career choices, reputations, etc.

Content

Inhalt: Metrics in Research - For better or worse? / Jozica Dolenc, Philippe Hünenberger Oliver Renn - A brief visual history of research metrics / Oliver Renn, Jozica Dolenc, Joachim Schnabl - Bibliometry: The wizard of O's / Philippe Hünenberger - The grip of bibliometrics - A student perspective / Matthias Tinzl - Honesty and transparency to taxpayers is the long-term fundament for stable university funding / Wendelin J. Stark - Beyond metrics: Managing the performance of your work / Charlie Rapple - Scientific profiling instead of bibliometrics: Key performance indicators of the future / Rafael Ball - More knowledge, less numbers / Carl Philipp Rosenau - Do we really need BIBLIO-metrics to evaluate individual researchers? / Rüdiger Mutz - Using research metrics responsibly and effectively as a researcher / Peter I. Darroch, Lisa H. Colledge - Metrics in research: More (valuable) questions than answers / Urs Hugentobler - Publication of research results: Use and abuse / Wilfred F. van Gunsteren - Wanted: Transparent algorithms, interpretation skills, common sense / Eva E. Wille - Impact factors, the h-index, and citation hype - Metrics in research from the point of view of a journal editor / Renato Zenobi - Rashomon or metrics in a publisher's world / Gabriella Karger - The impact factor and I: A love-hate relationship / Jean-Christophe Leroux - Personal experiences bringing altmetrics to the academic market / Ben McLeish - Fatally attracted by numbers? / Oliver Renn - On computable numbers / Gerd Folkers, Laura Folkers - ScienceMatters - Single observation science publishing and linking observations to create an internet of science / Lawrence Rajendran.

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Abstract

In this paper we analyze a major part of the research output of the Networked Knowledge Organization Systems (NKOS) community in the period 2000 to 2015 from a network analytical perspective. We fo- cus on the paper output presented at the European NKOS workshops in the last 15 years. Our open dataset, the "NKOS bibliography", includes 14 workshop agendas (ECDL 2000-2010, TPDL 2011-2015) and 4 special issues on NKOS (2001, 2004, 2006 and 2015) which cover 171 papers with 218 distinct authors in total. A focus of the analysis is the visualization of co-authorship networks in this interdisciplinary eld. We used standard network analytic measures like degree and betweenness centrality to de- scribe the co-authorship distribution in our NKOS dataset. We can see in our dataset that 15% (with degree=0) of authors had no co-authorship with others and 53% of them had a maximum of 3 cooperations with other authors. 32% had at least 4 co-authors for all of their papers. The NKOS co-author network in the "NKOS bibliography" is a typical co- authorship network with one relatively large component, many smaller components and many isolated co-authorships or triples.

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Abstract

Knowledge Organization (KO) theoretical foundations are still being developed in a continuous process of epistemological, theoretical and methodological consolidation. The remarkable growth of scientific records has stimulated the analysis of this production and the creation of instruments to evaluate the behavior of science became indispensable. We propose the Domain Analysis of KO in North America through the citation analysis of North American Symposium on Knowledge Organization (NASKO) proceedings (2007 - 2015). We present the citation, co-citation and bibliographic coupling analysis to visualize and recognize the researchers that influence the scholarly communication in this domain. The most prolific authors through NASKO conferences are Smiraglia, Tennis, Green, Dousa, Grant Campbell, Pimentel, Beak, La Barre, Kipp and Fox. Regarding their theoretical references, Hjørland, Olson, Smiraglia, and Ranganathan are the authors who most inspired the event's studies. The co-citation network shows the highest frequency is between Olson and Mai, followed by Hjørland and Mai and Beghtol and Mai, consolidating Mai and Hjørland as the central authors of the theoretical references in NASKO. The strongest theoretical proximity in author bibliographic coupling network occurs between Fox and Tennis, Dousa and Tennis, Tennis and Smiraglia, Dousa and Beak, and Pimentel and Tennis, highlighting Tennis as central author, that interconnects the others in relation to KO theoretical references in NASKO. The North American chapter has demonstrated a strong scientific production as well as a high level of concern with theoretical and epistemological questions, gathering researchers from different countries, universities and knowledge areas.

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Abstract

The VOSviewer software provides easy access to bibliometric mapping using data from Dimensions, Scopus and Web of Science. The properly formatted and structured citation data, and the ease in which it can be exported open up new avenues for use during citation searches and eference interviews. This paper details specific techniques for using advanced searches in Dimensions, exporting the citation data, and drawing insights from the maps produced in VOS Viewer. These search techniques and data export practices are fast and accurate enough to build into reference interviews for graduate students, faculty, and post-PhD researchers. The search results derived from them are accurate and allow a more comprehensive view of citation networks embedded in ordinary complex boolean searches.

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Content

Vgl. auch Open Password, Nr.167 vom 01.03.2017 :"Eugene Garfield, Begründer und Pionier der Zitationsindexierung und der Ziationsanalyse, ohne den die Informationswissenschaft heute anders aussähe, ist im Alter von 91 Jahren gestorben. Er hinterlässt Frau, drei Söhne, eine Tochter, eine Stieftochter, zwei Enkeltöchter und zwei Großelternkinder. Garfield machte seinen ersten Abschluss als Bachelor in Chemie an der Columbia University in New York City im Jahre 1949. 1954 sattelte er einen Abschluss in Bibliothekswissenschaft drauf. 1961 sollte er im Fach strukturelle Linguistik promovieren. Als Chemie-Student war er nach eigenen Angaben weder besonders gut noch besonders glücklich. Sein "Erweckungserlebnis" hatte er auf einer Tagung der American Chemical Society, als er entdeckte, dass sich mit der Suche nach Literatur womöglich ein Lebensunterhalt bestreiten lasse. "So I went to the Chairman of the meeting and said: "How do you get a job in this racket?" Ab 1955 war Garfield zunächst als Berater für pharmazeutische Unternehmen tätig. Dort spezialisierte er sich auf Fachinformationen, indem er Inhalte relevanter Fachzeitschriften erarbeitete. 1955 schlug er in "Science" seine bahnbrechende Idee vor, Zitationen wissenschaftlicher Veröffentlichungen systematisch zu erfassen und Zusammenhänge zwischen Zitaten deutlich zu machen. 1960 gründete Garfield das Institute für Scientific Informationen, dessen CEO er bis 1992 blieb. 1964 brachte er den Scientific Information Index heraus. Weitere Maßgrößen wie der Social Science Index (ab 1973), der Arts and Humanities Citation Index (ab 1978) und der Journal Citation Index folgten. Diese Verzeichnisse wurden in dem "Web of Science" zusammengefasst und als Datenbank elektronisch zugänglich gemacht. Damit wurde es den Forschern ermöglich, die für sie relevante Literatur "at their fingertips" zu finden und sich in ihr zurechtzufinden. Darüber hinaus wurde es mit Hilfe der Rankings von Garfields Messgrößen möglich, die relative wissenschaftliche Bedeutung wissenschaftlicher Beiträge, Autoren, wissenschaftlicher Einrichtungen, Regionen und Länder zu messen.
Garfield wandte sich im Zusammenhang mit seinen Messgrößen gegen "Bibliographic Negligence" und "Citation Amnesia", Er schrieb 2002: "There will never be a perfect solution to the problem of acknowledging intellectual debts. But a beginning can be made if journal editors will demand a signed pledge from authors that they have searched Medline, Science Citation Index, or other appropriate print and electronic databases." Er warnte aber auch vor einen unsachgemäßen Umgang mit seinen Messgößen und vor übertriebenen Erwartungen an sie in Zusammenhang mit Karriereentscheidungen über Wissenschaftler und Überlebensentscheidungen für wissenschaftliche Einrichtungen. 1982 übernahm die Thomson Corporation ISI für 210 Millionen Dollar. In der heutigen Nachfolgeorganisation Clarivate Analytics sind mehr als 4000 Mitarbeitern in über hundert Ländern beschäftigt. Garfield gründete auch eine Zeitung für Wissenschaftler, speziell für Biowissenschaftler, "The Scientist", die weiterbesteht und als kostenfreier Pushdienst bezogen werden kann. In seinen Beiträgen zur Wissenschaftspolitik kritisierte er beispielsweise die Wissenschaftsberater von Präsident Reagen 1986 als "Advocats of the administration´s science policies, rather than as objective conduits for communication between the president and the science community." Seinen Beitrag, mit dem er darum warb, die Förderung von UNESCO-Forschungsprogrammen fortzusetzen, gab er den Titel: "Let´s stand up für Global Science". Das ist auch in Trump-Zeiten ein guter Titel, da die US-Regierung den Wahrheitsbegriff, auf der Wissenschaft basiert, als bedeutungslos verwirft und sich auf Nationalismus und Abschottung statt auf internationale Kommunikation, Kooperation und gemeinsame Ausschöpfung von Interessen fokussiert."

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Abstract

I believe that Google Scholar is the most popular academic indexing way for researchers and citations. However, some other indexing institutions may be more professional than Google Scholar but not as popular as Google Scholar. Other indexing websites like Scopus and Clarivate are providing more statistical figures for scholars, institutions or even journals. On account of publication citations, always Google Scholar shows higher citations for a paper than other indexing websites since Google Scholar consider most of the publication platforms so he can easily count the citations. While other databases just consider the citations come from those journals that are already indexed in their database

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Type

a