A classification of multi-sensory metaphors for understanding abstract data in a virtual environment

With the advent of virtual environment technology, it is now possible to construct new styles of user interfaces that provide multi-sensory interactions. For example, interfaces can be designed which utilise 3D visual spaces and also provide auditory and haptic feedback. Many information spaces are multivariate, large and abstract in nature. It has been a goal of virtual environments to “widen the human-to-computer bandwidth” and so assist in the interpretation of these spaces by providing models that map different attributes of data to different senses. While this approach has the potential to assist in understanding these large information spaces, what is unclear is how to choose the best metaphors or models to define these mappings between the abstract information and the human sensory channels. This paper takes a look at some issues involved in choosing such multi-sensory metaphors, provides a classification of interactions and examines their application to the task of technical analysis of stock market data