Scientific advances today increasingly depend on understanding, manipulating and querying data. In addition, businesses that can capitalise on the value of information will have a competitive edge. This is especially true when businesses collect personal data: their ability to gain insight from it is dependent on compliance with complex, and often international, privacy laws. Typically, data has structure which can be described by formal mathematical statements called axioms. These axioms are typically written in symbolic, mathematical notations, which are inaccessible to most people. This is a serious shortcoming because ensuring the axioms are correct is particularly hard.

Our proposed solution represents a paradigm shift: we hypothesise that diagrams can be used instead of mathematical symbols to yield an accessible reasoning system. These diagrams are just as formal as the traditional mathematical approach. A particularly exciting aspect of our project is that it draws on both computer science and cognitive science, to address a long-held assumption that using diagrams makes modelling and reasoning accessible.

In addition to the rapid rise in quantity and availability of data, and the benefits this stands to bring to society if suitably understood, recent research has demonstrated that diagrams bring cognitive benefits over symbolic and textual notations. This cognitive offloading, identified using neuroscience approaches, shows that people find reasoning tasks significantly easier when using diagrams. These results mean that the time is right to design an accessible diagrammatic logic that is suitable for real-world modelling and reasoning.

The project is funded by the Leverhulme Trust and is a collaboration between the University of Cambridge led by Dr Mateja Jamnik and the University of Brighton led by Dr Gem Stapleton.