Online from: 1977
Subject Area: Library and Information Studies
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|Title:||Ranking and mapping of universities and research-focused institutions worldwide based on highly-cited papers: A visualisation of results from multi-level models|
|Author(s):||Lutz Bornmann, (Division for Science and Innovation Studies, Administrative Headquarters of the Max Planck Society, Munich, Germany), Moritz Stefaner, (Independent Researcher, Lilienthal, Germany), Felix de Moya Anegón, (Instituto de Políticas y Bienes Públicos, Consejo Superior de Investigaciones Científicas, Madrid, Spain), Rüdiger Mutz, (Swiss Federal Institute of Technology Zurich, Zurich, Switzerland)|
|Citation:||Lutz Bornmann, Moritz Stefaner, Felix de Moya Anegón, Rüdiger Mutz, (2014) "Ranking and mapping of universities and research-focused institutions worldwide based on highly-cited papers: A visualisation of results from multi-level models", Online Information Review, Vol. 38 Iss: 1, pp.43 - 58|
|Keywords:||Geography of science, Google Maps, Highly-cited papers, Scientific excellence, Spatial scientometrics, University ranking|
|Article type:||Research paper|
|DOI:||10.1108/OIR-12-2012-0214 (Permanent URL)|
|Publisher:||Emerald Group Publishing Limited|
Purpose – The web application presented in this paper allows for an analysis to reveal centres of excellence in different fields worldwide using publication and citation data. Only specific aspects of institutional performance are taken into account and other aspects such as teaching performance or societal impact of research are not considered. The purpose of this paper is to address these issues.
Design/methodology/approach – Based on data gathered from Scopus, field-specific excellence can be identified in institutions where highly-cited papers have been frequently published.
Findings – The web application (www.excellencemapping.net) combines both a list of institutions ordered by different indicator values and a map with circles visualising indicator values for geocoded institutions.
Originality/value – Compared to the mapping and ranking approaches introduced hitherto, our underlying statistics (multi-level models) are analytically oriented by allowing the estimation of values for the number of excellent papers for an institution which are statistically more appropriate than the observed values; the calculation of confidence intervals as measures of accuracy for the institutional citation impact; the comparison of a single institution with an “average” institution in a subject area: and the direct comparison of at least two institutions.
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