Ranking Universities Using Linked Open Data

Ranking of universities represents a complex endeavor which involves gathering, weighting, and analyzing diverse data. Emerging semantic technologies enable the Web of Data, a giant graph of interconnected information resources, also known as Linked Data. A recent community effort, Linking Open Data project, offers the possibility of accessing a large number of semantically described and linked concepts in various domains. In this paper, we propose a novel approach to take advantage of this structured data in the domain of universities to develop proxy measures of their relative standing for ranking purposes. Derived from information theory, our approach of computing the Information Content for universities and ranking them based on these scores achieved results comparable to the international ranking systems such as Shanghai Jiao Tong University, Times Higher Education, and QS. The metric we developed can also be used for innovative semantic applications in a range of domains for entity ranking, information filtering, and multi-faceted browsing.