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Abstract

In einer szientometrischen bzw. informetrischen Studie werden internationale wie deutschsprachige Zeitschriften der Informations-/Bibliothekswissenschaft und -praxis mittels Zitationsanalyse und Expertenbefragung analysiert. Die zitatenanalytischen Kennwerte umfassen den Impact Factor, die Halbwertszeit, die Zitierfreudigkeit, die relative Häufigkeit von Zeitschriftenselbstreferenzen sowie Soziogramme der einflussreichen Periodika. Der Fragebogen erhebt die Lesehäufigkeit, die Einsetzbarkeit der gelesenen Journale im Tätigkeitsbereich, die Publikationstätigkeit und die Publikationspräferenz sowohl für alle Respondenten als auch für abgrenzbare Gruppen (Praktiker vs. Wissenschaftler, Bibliothekare vs. Dokumentare vs. Informationswissenschaftler, öffentlicher Dienst vs. Informationswirtschaft vs. andere Wirtschaftsunternehmen).

Series

Kölner Arbeitspapiere zur Bibliotheks- und Informationswissenschaft; Bd.33

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Abstract

Die empirische Wissenschaftsforschung arbeitet bei den Indikatoren wissenschaftlicher Leistung und wissenschaftlicher Wirkung mit Publikations- und Zitationsraten. Die vorliegende Arbeit befaßt sich mit dabei auftretenden methodischen Problemen. Was ist überhaupt eine Publikation? Was heißt Zitation? Zentral ist auch die Zählbasis, d.h. die Einheitenbildung: Was ist 1 Publikation? und: Was ist 1 Zitation? Bei Printpublikationen gibt es eine Reihe von beachtenswerten Faktoren (u.a. Mehrautorenwerke, Gewichtungsfaktoren wie den Impact Factor, Dokumenttypen). Bei elektronischen Publikationen im Internet mit ihrem dynamischen Charakter ist die Einheitenbildung noch weitaus problematischer. Zitationen, verstanden als zitierte Publikationen, werfen alle methodischen Probleme der Publikationseinheiten auf, hinzu kommen weitere, spezifische Probleme. Lösungsmöglichkeiten im syntaktischen Bereich (Relativierung auf Textseiten oder Zeichen) ändern am grundlegenden Problem nur wenig, Lösungsversuche im semantischen Bereich (etwa im Rahmen der semantischen Informationstheorie) sind im Rahmen der Publikations- und Zitationsanalysen nicht durchführbar und verweisen sowohl auf themenanalytische Methoden als auch auf die Wissenschaftstheorie. Mit diesem Working Paper wollen wir vor allem auf offene Probleme hinweisen; "endgültige" Lösungen wird der Leser nicht finden, wohl aber Lösungsvorschläge, die meist durchaus noch diskussionswürdig sind. In der Informationswissenschaft wie in der Wissenschaftsforschung sind wir bisher viel zu sicher davon ausgegangen, daß wir wissen, was Publikationen und Zitationen sind

Imprint

Köln : FH Köln, Fachbereich Bibliotheks- und Informationswesen

Series

Kölner Arbeitspapiere zur Bibliotheks- und Informationswissenschaft; Bd.29

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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.

Content

Der vollständige Bericht ist im Internet unter der folgenden Adresse zugänglich: http://www.mathunion.org/fileadmin/IMU/Report/CitationStatistics.pdf. - Vgl. auch den Beitrag: Zitaten-Statistiken. In: Mitteilungen der Deutschen Mathematiker-Vereinigung. 2008, H.3, S.198-203.