We've been working on a systematic framework to guide choice of appropriate representation technique for different purposes. Although some aspects of this issue have already been covered by the field of knowledge representation within Artificial Intelligence, and by Tufte's work on graphical representations, there's a need for a framework that's broader than the one in knowledge representation, and more theoretically grounded than the one in Tufte's work.
The diagram below shows an example from our work. It takes two concepts that are usually viewed as opposites (liking and disliking) and treats them as two separate dimensions, both running from low to high.
are useful not only for eliciting information, but also for showing the mental categories that people use.
is a way of representing knowledge that's very different from nested boxes or hierarchies.
makes it possible to use more than one categorisation for the same topic at the same time.
between categories are common; this article describes ways of representing them visually.
is complex; this article shows ways of representing set theory via richer visualisations.
is invaluable for representing networks, and chains of connections. This article is a brief introduction.
are a useful notation for recording sequences of activities.
Trees and nets
are concepts from graph theory that are invaluable for expressing concepts more rigorously.