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.

大学提供的教育质量和研究影响不断在国家和国际层面进行评估。这种现象并不新鲜。然而，如今教育不仅被视为一种社会价值和权利/特权，而且被视为一个重要的经济部门，面向全球大部分人口。在这个生态系统中，大学排名发挥着至关重要的作用，因为它们提供了在调查、报纸、社交媒体等中复制的过滤信息。所有大学排名都基于一组临时评估标准。此外，最终分数是基于一组任意权重总和为 1。因此，最终，这些大学排名差异很大，产生了歧义和疑问。在本文中，我们提出了一种基于 Skyline 算子的新型大学排名方法，该方法用于多维对象以提取非支配（即“流行”）对象。我们的方法具有几个优点，例如：它是透明的、可重复的、没有任何任意选择的参数、仅基于大学的研究成果，而不是基于公开不可追踪的或问卷调查。我们的方法不提供绝对排名，而是对归类为等价类的大学进行排名。因此，我们开发了一个通用框架，可用于对大学和院系甚至个人进行排名。对于概念证明，我们在希腊学术空间中应用了该框架，