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In the Head of the Beholder: Comparing Different Proof Representations

Christian Alrabbaa; Stefan Borgwardt; Anke Hirsch; Nina Knieriemen; Alisa Kovtunova; Anna Milena Rothermel; Frederik Wiehr
In: Guido Governatori; Anni-Yasmin Turhan (Hrsg.). Rules and Reasoning. International Joint Conference on Rules and Reasoning (RuleML+RR-2022), Cham, Pages 211-226, ISBN 978-3-031-21541-4, Springer International Publishing, 2022.


Ontologies provide the logical underpinning for the Semantic Web, but their consequences can sometimes be surprising and must be explained to users. A promising kind of explanations are proofs generated via automated reasoning. We report about a series of studies with the purpose of exploring how to explain such formal logical proofs to humans. We compare different representations, such as tree- vs. text-based visualizations, but also vary other parameters such as length, interactivity, and the shape of formulas. We did not find evidence to support our main hypothesis that different user groups can understand different proof representations better. Nevertheless, when participants directly compared proof representations, their subjective rankings showed some tendencies such as that most people prefer short tree-shaped proofs. However, this did not impact the user's understanding of the proofs as measured by an objective performance measure.