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Details of Grant 

EPSRC Reference: EP/R043949/1
Title: The Applied Semiotics of Visual Modelling
Principal Investigator: Burton, Dr J
Other Investigators:
Researcher Co-Investigators:
Project Partners:
Department: Sch of Computing, Engineering & Maths
Organisation: University of Brighton
Scheme: Discipline Hopping Awards
Starts: 01 October 2018 Ends: 30 September 2019 Value (£): 71,393
EPSRC Research Topic Classifications:
Computer Graphics & Visual.
EPSRC Industrial Sector Classifications:
Information Technologies
Related Grants:
Panel History:
Panel DatePanel NameOutcome
02 May 2018 EPSRC ICT Prioritisation Panel May 2018 Announced
Summary on Grant Application Form
In the digital age, every member of society needs to process, interrogate and understand

complex data. In addition, more and more of us take part in or depend on specialised fields in which

information has to be absolutely precise, such as the design and creation of

software. Graphical forms of communication are widely recognised as an effective way of

communicating certain types of information, whether through a simple data visualisation such as

a bar chart accompanying a newspaper article, or through a complex diagram which specifies a

computer system. Thus, there are many benefits inherent to understanding how these graphical

forms work, and what makes them more or less effective (relative to, say, the written word) for

certain tasks.

Semiotics is the perspective that analyses these graphical notations as so many arrangements of

signs. The field of semiotics began with the work of Charles Peirce, who provided a richly

thorough analysis of the types of signs, their components, the relations of the components to

one another and so on. Despite several initial approaches and numerous differing perspectives

on the same problem, no one has yet applied the semiotic method in depth to the analysis of

diagrammatic languages to make predictions of their cognitive potentials; that is what this

project sets out to do.

We will begin by analysing several widely used data visualisations, including those which are

used interactively, from a Peircean perspective. That is, we will use Peirce's classification

of types of sign and their correlation with different types of information to make predictions

about the potential effectiveness and suitability of the visualisations for particular

tasks. We will correlate these predictions with findings from cognitive science and HCI, where

such visualisations are studied from different points of view. This evaluation will result in

guidelines for the use of existing techniques and generalised criteria for the design of data

visualisations.

The next step in our project is to use the frame of reference explained above to analyse the

logic of concept diagrams. Concept diagrams were designed for knowledge representation and have

been found to be more effective than symbolic alternatives for some tasks. A diagrammatic logic

is more than data visualisation; it is a precisely defined graphical notation (e.g. Venn

diagrams or concept diagrams), together with a set of rules for transforming and possibly

combining diagrams in logically valid ways. Although they are not a panacea, when diagrammatic

logics are used in place of "traditional" symbolic alternatives, certain advantages can arise:

in some circumstances a diagram effectively reveals more information than was required for its

construction. This is a key source of the power of diagrammatic communication, whereby

information is revealed "by construction" that would need to be inferred as a result of some

chain of reasoning if the information were presented in a symbolic language. The means by which

this takes place are a central part of Peircean semiotics, and are also of great interest to

disciplines outside semiotics, such as human-computer interaction and cognitive science. One of

our contributions will be our attempt to reconcile and find agreements or inconsistencies among

these different accounts of the "natural" or "intuitive" power of diagrams and data

visualisation. In this way, we aim to enable people to make better use of existing notations

and design more effective notations for the future.
Key Findings
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Potential use in non-academic contexts
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Impacts
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Summary
Date Materialised
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Further Information:  
Organisation Website: http://www.bton.ac.uk