Accessible Reasoning with Diagrams

  • Stapleton, Gem, (PI)
  • Jamnik, Mateja (PI)
  • Oliver, Ian (CoI)
  • Bonnington, Adrienne (CoI)
  • Benzmueller, Christoph (CoI)
  • Narayanan, Hari (CoI)

Description

Advances in scientific research are increasingly dependent on the analysis of ever larger datasets. However, the traditional mathematical logics used to represent, model and reason about information are inaccessible to most people. Modelling modern high-technology systems is complex and involves multiple stakeholders. As these systems increasingly underpin our everyday lives, and are often safety or security critical, reasoning about correctness is paramount.

By combining approaches from computer science and cognitive science, we aim to develop a novel and accessible diagram-based logic that is suitable for information representation and reasoning across a wide range of subject areas. The tools we develop will enable better communication and understanding between those who produce the models, and those who use them, and ultimately lead to more robust and effective models to underpin scientific research.

Modelling and formal reasoning is required in order to convey knowledge unambiguously and correctly. Whilst mathematical modelling adds great rigour, it is opaque to many of the stakeholders. This leads to errors in data handling, delays in product release, and even breaches in consumer privacy. We propose a solution: a new formal diagrammatic approach for developing, debugging, communicating and reasoning rigorously yet accessibly about domain models. Thus, the hypothesis for our project “ARD: Accessible Reasoning with Diagrams”, which challenges the existing symbolic paradigm, is:

It is possible to devise an accessible diagrammatic logic for modelling and reasoning in diverse domains.

Uniquely, the development of this diagrammatic approach will be guided by extensive empirical studies of what humans understand and find accessible. Whilst pushing forward research into diagrams and logic, a major goal is also to bring usable reasoning tools to end-users who need to understand, develop and reason about models of their respective domains.

Key findings

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 collaborative project with the University of Cambridge. The Investigators are Dr Gem Stapleton, Reader in Computer Science at the University of Brighton, and Dr Mateja Jamnik, Senior Lecturer at the University of Cambridge.

This project marries two different fields, computer science and cognitive science. A unique aspect is the use of empirical studies to guide the development of foundational approaches to reasoning.

The major research contributions fall within two main streams:

Stream 1: diagrammatic reasoning, led by Mateja Jamnik, University of Cambridge

Stream 2: empirical evaluation, led by Gem Stapleton, University of Brighton

The objectives are to:

-develop case studies to identify core modelling and reasoning problems (Streams 1 and 2)
-qualitatively identify effective diagrammatic representations (Stream 2 )
-design an accessible diagrammatic logic for modelling and visual reasoning (Stream 1)
-develop empirically informed layout algorithms for diagrams (Stream 2 )
-implement a reasoning system for our diagrammatic representations (Stream 1
-test and empirically evaluate the accessibility of our system (Streams 2 and 1)

These objectives will be achieved by teaming two groups (for three years, employing a postdoc at each site) with the interdisciplinary expertise necessary for delivering world-leading contributions to diagrammatic reasoning and cognitive science.

Reducing miscommunication between disparate groups and improving model accuracy removes key risks relating to the processing of data, including safety or security implications. One example is in the area of personal privacy, which is of high importance to commerce and society because of the significant risks and costs associated with data misuse. The scale of potential losses can be extremely large, exceeding tens of millions of Euros, in addition to the immeasurable financial implications caused by reputational damage. However, at present, companies such as Nokia cannot devote the resources required to deliver (possibly risky) blue skies research, as it requires specialist expertise and is distant from commercialisation.

It is anticipated that as a result of this project, Nokia will be able to make rapid use of concept diagrams, potentially avoiding costly delays in production. Nokia and all of the end-users of their services will directly and immediately benefit through better specified privacy protection mechanisms. The fact that there are millions of Nokia end-users demonstrates the level and scale of impact that will be achieved by this research on diagrammatic logics. By extension, these types of benefits will arise for all end-users of our research.

Our results will also impact on basic research in computer science and in cognitive science. For the first time, a logic will be designed and implemented with human understanding and accessibility at the fore. Our results will give significant insight into human reasoning and which aspects of logic people find intuitive.
AcronymARD
StatusFinished
Effective start/end date1/09/1631/08/19