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Issue title: Model and Data Engineering, MEDI 2016 Special Issue
Guest editors: Ladjel Bellatreche and Zbigniew W. Ras
Article type: Research Article
Authors: Savić, Miloša; * | Ivanović, Mirjanaa | Radovanović, Miloša | Surla, Bojana Dimićb
Affiliations: [a] University of Novi Sad, Faculty of Sciences, Trg Dositeja Obradovića 4, 21000 Novi Sad, Serbia, {svc, mira, radacha}@dmi.uns.ac.rs | [b] Union University, School of Computing Knez Mihailova 6, 11000 Belgrade, Serbia, bdimicsurla@raf.rs
Correspondence: [*] Address for correspondence: University of Novi Sad, Faculty of Sciences, Department of Mathematics and Informatics, Trg Dositeja Obradovića 4, 21000 Novi Sad, Serbia
Abstract: Current Research Information Systems (CRISs) offer great opportunities for assessments of institutional research outputs and extraction of useful and actionable knowledge based on various data-analysis techniques. However, many of these opportunities have not been explored in depth, especially in culture-sensitive areas such as gender-based analysis of research productivity and collaboration. In this paper we present GERBER, a network-based methodology and accompanying tool for gender-based analysis of publication data stored in institutional CRISs. GERBER relies on statistically robust techniques applied on weighted co-authorship networks whose nodes are enriched with different types of researcher evaluation metrics. The functionality of GERBER is demonstrated on publication data stored in the institutional CRIS of the Faculty of Sciences, University of Novi Sad, Serbia. The obtained results show that GERBER enables institutional research managers and policy makers to detect gender inequalities and homophily in research productivity and collaboration. Finally, we discuss different possibilities to integrate GERBER with CRISs in order to facilitate continuous gender-based evaluation of researchers.
Keywords: research information systems, research productivity, research collaboration, genderbased analysis, gender inequalities, institutional analysis
DOI: 10.3233/FI-2018-1724
Journal: Fundamenta Informaticae, vol. 162, no. 4, pp. 237-258, 2018
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