Accessible Reasoning with Diagrams: From Cognition to Automation

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10871)


High-tech systems are ubiquitous and often safety and security critical: reasoning about their correctness is paramount. Thus, precise modelling and formal reasoning are necessary in order to convey knowledge unambiguously and accurately. Whilst mathematical modelling adds great rigour, it is opaque to many stakeholders which leads to errors in data handling, delays in product release, for example. This is a major motivation for the development of diagrammatic approaches to formalisation and reasoning about models of knowledge. In this paper, we present an interactive theorem prover, called iCon, for a highly expressive diagrammatic logic that is capable of modelling OWL 2 ontologies and, thus, has practical relevance. Significantly, this work is the first to design diagrammatic inference rules using insights into what humans find accessible. Specifically, we conducted an experiment about relative cognitive benefits of primitive (small step) and derived (big step) inferences, and use the results to guide the implementation of inference rules in iCon.



This research was funded by a Leverhulme Trust Research Project Grant (RPG-2016-082) for the project entitled Accessible Reasoning with Diagrams. The authors would like to thank Prof. John Howse, Dr Andrew Blake and Dr Ryo Takemura for their cooperation in the experiments.


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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Computer Science and TechnologyUniversity of CambridgeCambridgeUK
  2. 2.Centre for Secure, Intelligent and Usable SystemsUniversity of BrightonBrightonUK

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