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  • × theme_ss:"Informetrie"
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  1. Gutierres Castanha, R.C.; Hilário, C.M.; Araújo, P.C. de; Cabrini Grácio, M.C.: Citation analysis of North American Symposium on Knowledge Organization (NASKO) Proceedings (2007-2015) (2017) 0.01
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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.
  2. Van der Veer Martens, B.: Do citation systems represent theories of truth? (2001) 0.01
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    Date
    22. 7.2006 15:22:28
  3. Lamb, I.; Larson, C.: Shining a light on scientific data : building a data catalog to foster data sharing and reuse (2016) 0.01
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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.
  4. Williams, B.: Dimensions & VOSViewer bibliometrics in the reference interview (2020) 0.01
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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.
  5. Scientometrics pioneer Eugene Garfield dies : Eugene Garfield, founder of the Institute for Scientific Information and The Scientist, has passed away at age 91 (2017) 0.01
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    Content
    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."
  6. Adler, R.; Ewing, J.; Taylor, P.: Citation statistics : A report from the International Mathematical Union (IMU) in cooperation with the International Council of Industrial and Applied Mathematics (ICIAM) and the Institute of Mathematical Statistics (IMS) (2008) 0.00
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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.
  7. Herb, U.: Überwachungskapitalismus und Wissenschaftssteuerung (2019) 0.00
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    Content
    Der Text ist eine überarbeitete Version des von Herb, U. (2018): Zwangsehen und Bastarde : Wohin steuert Big Data die Wissenschaft? In: Information - Wissenschaft & Praxis, 69(2-3), S. 81-88. DOI:10.1515/iwp-2018-0021.
  8. Krattenthaler, C.: Was der h-Index wirklich aussagt (2021) 0.00
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    Content
    Vgl.: DOI: 10.1515/dmvm-2021-0050. Auch abgedruckt u.d.T.: 'Der h-Index - "ein nutzloser bibliometrischer Index"' in Open Password Nr. 1007 vom 06.12.2021 unter: https://www.password-online.de/?mailpoet_router&endpoint=view_in_browser&action=view&data=WzM3NCwiZDI3MzMzOTEwMzUzIiwwLDAsMzQ4LDFd.
  9. Harzing, A.-W.: Comparing the Google Scholar h-index with the ISI Journal Impact Factor (2008) 0.00
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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.
  10. Klein, A.: Von der Schneeflocke zur Lawine : Möglichkeiten der Nutzung freier Zitationsdaten in Bibliotheken (2017) 0.00
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    Abstract
    Zitationen spielen eine wichtige Rolle im wissenschaftlichen Diskurs, in der Recherchepraxis sowie im Bereich der Bibliometrie. In jüngster Zeit gibt es zunehmend Initiativen, die Zitationen als Open Data zur freien Nachnutzung verfügbar machen. Der Beitrag beschreibt den Stand der Entwicklung dieser Initiativen und zeigt, dass in nächster Zeit eine kritische Masse von Daten entstehen könnte, aus denen sich gerade für Bibliotheken neue Perspektiven ergeben. Als konkrete Möglichkeit zur Partizipation für Bibliotheken wird das DFG-Projekt Linked Open Citation Database (LOC-DB) vorgestellt.
  11. Braun, S.: Manifold: a custom analytics platform to visualize research impact (2015) 0.00
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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.
  12. Metrics in research : for better or worse? (2016) 0.00
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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.