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OpenRank – a novel approach to rank universities using objective and publicly verifiable data sources

Muhammad Sajid Qureshi (Department of Computer Science and Software Engineering, International Islamic University, Islamabad, Pakistan) (Department of Software Engineering, Foundation University Islamabad, Rawalpindi, Pakistan)
Ali Daud (Department of Computer Science and Software Engineering, International Islamic University, Islamabad, Pakistan) (Department of Computer Science and Artificial Intelligence, College of Computer Science and Engineering, University of Jeddah, Jeddah, Saudi Arabia)
Malik Khizar Hayat (Department of Information Technology, Faculty of Information Technology and Engineering, The University of Haripur, Haripur, Pakistan)
Muhammad Tanvir Afzal (Department of Computer Science, NAMAL Institute, Mianwali, Pakistan)

Library Hi Tech

ISSN: 0737-8831

Article publication date: 1 January 2021

Issue publication date: 1 June 2023

327

Abstract

Purpose

Academic rankings are facing various issues, including the use of data sources that are not publicly verifiable, subjective parameters, a narrow focus on research productivity and regional biases and so forth. This research work is intended to enhance creditability of the ranking process by using the objective indicators based on publicly verifiable data sources.

Design/methodology/approach

The proposed ranking methodology – OpenRank – drives the objective indicators from two well-known publicly verifiable data repositories: the ArnetMiner and DBpedia.

Findings

The resultant academic ranking reflects common tendencies of the international academic rankings published by the Shanghai Ranking Consultancy (SRC), Quacquarelli Symonds (QS) and Times Higher Education (THE). Evaluation of the proposed methodology advocates its effectiveness and quick reproducibility with low cost of data collection.

Research limitations/implications

Implementation of the OpenRank methodology faced the issue of availability of the quality data. In future, accuracy of the academic rankings can be improved further by employing more relevant public data sources like the Microsoft Academic Graph, millions of graduate's profiles available in the LinkedIn repositories and the bibliographic data maintained by Association for Computing Machinery and Scopus and so forth.

Practical implications

The suggested use of open data sources would offer new dimensions to evaluate academic performance of the higher education institutions (HEIs) and having comprehensive understanding of the catalyst factors in the higher education.

Social implications

The research work highlighted the need of a purposely built, publicly verifiable electronic data source for performance evaluation of the global HEIs. Availability of such a global database would help in better academic planning, monitoring and analysis. Definitely, more transparent, reliable and less controversial academic rankings can be generated by employing the aspired data source.

Originality/value

We suggested a satisfying solution for improvement of the HEIs' ranking process by making the following contributions: (1) enhancing creditability of the ranking results by merely employing the objective performance indicators extracted from the publicly verifiable data sources, (2) developing an academic ranking methodology based on the objective indicators using two well-known data repositories, the DBpedia and ArnetMiner and (3) demonstrating effectiveness of the proposed ranking methodology on the real data sources.

Keywords

Citation

Qureshi, M.S., Daud, A., Hayat, M.K. and Afzal, M.T. (2023), "OpenRank – a novel approach to rank universities using objective and publicly verifiable data sources", Library Hi Tech, Vol. 41 No. 2, pp. 474-500. https://doi.org/10.1108/LHT-07-2019-0131

Publisher

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Emerald Publishing Limited

Copyright © 2020, Emerald Publishing Limited

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