Georgios Stoupas, Antonis Sidiropoulos, Dimitrios Katsaros, Y. Manolopoulos
{"title":"When universities rise (Rank) high into the skyline","authors":"Georgios Stoupas, Antonis Sidiropoulos, Dimitrios Katsaros, Y. Manolopoulos","doi":"10.1080/09737766.2021.1955419","DOIUrl":null,"url":null,"abstract":"The quality of the education provided and the research impact produced by universities is continuously evaluated at national and international level. This phenomenon is not new. However, nowadays education is not only considered as a social value and right/privilege, but also as a big economic sector, which addresses to large portions of population worldwide. In this ecosystem, university rankings play a crucial role since they provide filtered information which is reproduced in surveys, newspapers, social media etc. All university rankings are based on a set of ad hoc evaluation criteria. Moreover, the final score is based on a set of arbitrary weights summing up to 1. Thus, at the end, these university rankings differ significantly producing ambiguities and doubts. In this paper, we propose a novel university ranking method based on the Skyline operator, which is used on multi-dimensional objects to extract the non-dominated (i.e., “prevailing”) ones. Our method is characterized by several advantages, such as: it is transparent, reproducible, without any arbitrarily selected parameters, based on the research output of universities only and not on publicly not traceable or questionnaires. Our method does not provide absolute rankings, but rather it ranks universities categorized in equivalence classes. Thus, we develop a generic framework which can be used for ranking universities and departments, and even individual persons. For the proof of concept we apply the framework in our Greek academic space, providing a case study on ranking persons and departments on computer science and engineering using data extracted from Microsoft Academic.","PeriodicalId":10501,"journal":{"name":"COLLNET Journal of Scientometrics and Information Management","volume":"15 1","pages":"241 - 258"},"PeriodicalIF":1.6000,"publicationDate":"2021-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"COLLNET Journal of Scientometrics and Information Management","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/09737766.2021.1955419","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"INFORMATION SCIENCE & LIBRARY SCIENCE","Score":null,"Total":0}
引用次数: 1
Abstract
The quality of the education provided and the research impact produced by universities is continuously evaluated at national and international level. This phenomenon is not new. However, nowadays education is not only considered as a social value and right/privilege, but also as a big economic sector, which addresses to large portions of population worldwide. In this ecosystem, university rankings play a crucial role since they provide filtered information which is reproduced in surveys, newspapers, social media etc. All university rankings are based on a set of ad hoc evaluation criteria. Moreover, the final score is based on a set of arbitrary weights summing up to 1. Thus, at the end, these university rankings differ significantly producing ambiguities and doubts. In this paper, we propose a novel university ranking method based on the Skyline operator, which is used on multi-dimensional objects to extract the non-dominated (i.e., “prevailing”) ones. Our method is characterized by several advantages, such as: it is transparent, reproducible, without any arbitrarily selected parameters, based on the research output of universities only and not on publicly not traceable or questionnaires. Our method does not provide absolute rankings, but rather it ranks universities categorized in equivalence classes. Thus, we develop a generic framework which can be used for ranking universities and departments, and even individual persons. For the proof of concept we apply the framework in our Greek academic space, providing a case study on ranking persons and departments on computer science and engineering using data extracted from Microsoft Academic.