What is the effect of country-specific characteristics on the research performance of scientific institutions? Using multi-level statistical models to rank and map universities and research-focused institutions worldwide

Abstract

Bornmann, Stefaner, de Moya Anegón, and Mutz (2014) have introduced a web application (www.excellencemapping.net) which is linked to both academic ranking lists published hitherto (e.g. the Academic Ranking of World Universities) as well as spatial visualization approaches. The web application visualizes institutional performance within specific subject areas as ranking lists and on custom tile-based maps. The new, substantially enhanced version of the web application and the generalized linear mixed model for binomial data on which it is based are described in this paper. Scopus data were used which have been collected for the SCImago Institutions Ranking. Only those universities and research-focused institutions are considered that have published at least 500 articles, reviews and conference papers in the period 2006 to 2010 in a certain Scopus subject area. In the enhanced version, the effect of single covariates (such as the per capita GDP of a country in which an institution is located) on two performance metrics (best paper rate and best journal rate) is examined and visualized.A covariate-adjusted ranking and mapping of the institutions is produced in which the single covariates are held constant. The results on the performance of institutions can then be interpreted as if the institutions all had the same value (reference point) for the covariate in question. For example, those institutions can be identified worldwide showing a very good performance despite a bad financial situation in the corresponding country.

Making Scientometric Sense out of NIRF Scores

“…THE National Institutional Ranking Framework (NIRF) has just released its maiden rankings of higher educational institutions across the country. Unlike other international university ranking schemes which are based on educational and research excellence [1][2][3][4] , here very broad but often fuzzy parameters are used which cover aspects classified broadly under the heads 'Teaching, Learning and Resources', 'Research and Professional Practices', 'Graduation Outcomes', 'Outreach and Inclusivity', and 'Perception'. These five broad heads are then elaborated through further sub-heads, with weights assigned to each broad head, and more weights assigned to the sub-heads within each head.…”

“…We use the bibliometric data that has been released through the NIRF 2016 rankings to see how the top twenty engineering institutions fare if only research excellence is considered as is done in major ranking exercises [1][2][3][4] . Unlike the NIRF score, which is one single number, we now decompose performance into a sizedependent exergy term and a size-independent productivity term.…”

Excellence and Diversity Mapping of Research in IISc, IITs, NUS and NTU

“…The latest and fourth release of the web application (http://www.excellencemapping.net/#/view/measure/top10/ calculation/a_ohne_kovariable/field/materials-science/significant/false/org/) based on articles during the five-year publication window 2008-12 visualizes scientific excellence worldwide in 22 major subject areas [2][3][4] . These subject areas are covered by Scopus data as collected for the SCImago Institutions Ranking (http://www.scimagoir.…”

“…BPR corresponds to PP (top 10%) used in the Leiden Ranking and the excellence rate used in the SCImago Institutions Ranking 6 . The excellence rate is a field-normalized sizeindependent indicator which serves as a measure of the high quality output of research institutions [2][3][4] . A singlevalued composite outcome indicator for the research performance of each unit of assessment can be computed as the second-order indicator 7 called the exergy term from the quantity (size) and quality (excellence) indicators, x = i 2 P. In the second stage we examine the variance in performance of the units within a larger aggregation.…”

“…The present work attempts to use the ABCD matrix formulation to describe the Z-scan technique to determine the nonlinear response of a material. There are several methods to measure nonlinear refraction including nonlinear interferometry 3,4 , degenerate four-wave mixing 5 , degenerate three-wave mixing 6 , ellipse rotation 7 , and beam distortion measurements 8 and Zscan 9,10 . The first three methods are potentially sensitive techniques, but these require relatively complex experimental apparatus, whereas Z-scan is a simple technique to study nonlinear refraction and nonlinear absorption.…”