IEEE Symposium on Visual Languages
September 10-14, 2000
|Tutorial T1 -||Diagrammatic Reasoning and Visual Languages|
|Corin Gurr (University of Edinburgh, Scotland)|
Sunday, September 10, 8:30 AM
Diagrams are pictorial, yet abstract, representations of information. Diagrammatic representation and reasoning is a recently rejuvenated are of research that is concerned with how humans or machines can represent information using diagrams, and then reason (solve problems with, answer questions from, etc.) using those diagrams.
The tutorial commences by addressing the question: What is a diagram (and what is not)? Next we survey the history of approaches to understanding diagrammatic reasoning. The very richness of diagrams is illustrated by the diversity of fields in which they have been studied; including art, philosophy, psychology, mathematics, graphic design, AI, cognitive science, semiotics, engineering, and visual (programming) languages. More recent studies of diagrammatic communication (which encompasses representation, reasoning and interaction) may be broadly classified into three categories:
The tutorial will provide an overview of historical and contemporary research in the above areas, and will report on more recent work which attempts to unify these differing approaches. The tutorial concludes with a view of the current state of the art for theories of diagrams, a view to the near future, and summaries remaining open issues.
The tutorial should be accessible to all open-minded and interested participants.
Corin Gurr is a researcher who combines a background in theoretical Computer Science and AI with a broad understanding of Cognitive Science approaches to the understanding of human communication and reasoning. He has spent the last six years in the Human Communication Research Centre at the University of Edinburgh, studying issues of human communication and reasoning, particularly in domains where complex information is distributed amongst numerous cross-disciplinary participants. This work combines semantic and cognitive accounts of representations - and how human users react to them - and is informed through empirical and observational analysis, both of industrial best practice in software engineering and of more general human reasoning. This research includes: