Ranking and mapping of universities and research-focused institutions worldwide based on highly-cited papers is a research paper published in Online Information Review (2014). On theSindex it has a DataRank of 0.590. It has been cited 50 times.
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.
FAIR checklist signals are shown for context only and do not affect DataRank scoring.
Base Score Contribution
0.590
From this paper's citation signal
Citation Network Contribution
0
Citation network not refreshed for this result
This paper's DataRank is currently driven only by its base citation score. Citation network data was not refreshed for this result.
Learn more about DataRank methodology →DataRank blends this paper's own citation count with the influence of the papers that cite it. Here, roughly 100% comes from its base citations and 0% from the citation network.
Citers are pulled from OpenAlex sorted by cited_by_count:descand capped per paper, so when the cap binds we keep the highest-signal references and the score is reproducible across reruns.