A Method for Performing Ontology-Based Computational Literature Reviews Exemplified for Design Science Research

Sebastian Huettemann (), Roland M. Mueller () and Barbara Dinter ()
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Sebastian Huettemann: Berlin School of Economics and Law
Roland M. Mueller: Berlin School of Economics and Law
Barbara Dinter: Chemnitz University of Technology

A chapter in Shaping the Digital Future Through Innovation and Practice, 2026, pp 119-134 from Springer

Abstract: Abstract The traditional process of conducting literature reviews requires a significant amount of manual work and is often constrained by the limitations of small sample sizes. Although novel computational approaches to language analysis offer great opportunities, they are rarely applied to literature reviews. We aim to demonstrate the potential of ontology-based computational literature reviews. Therefore, we conducted a Design Science Research (DSR) project to apply and extend a method for this type of review. Since DSR shows a considerable diversity in theoretical foundations and methodological approaches and can serve as an insightful example, we first developed a machine learning classifier to identify DSR articles. Second, we applied and extended a method for ontological annotation and sentence classification. Finally, we conducted a computational literature review of 6235 DSR articles, focusing on the distribution of theories, methods, and topics. We also developed an interactive dashboard prototype with selected results from our study.

Keywords: Design science research; Computational literature review; Knowledge extraction; Knowledge synthesis (search for similar items in EconPapers)
Date: 2026
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DOI: 10.1007/978-3-032-08489-7_9

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