The rapid increase in available information has lead to many attempts to automatically locate patterns in large, abstract, multi-attributed information spaces. These techniques are often called data mining and have met with varying degrees of success. An alternative approach to automatic pattern detection is to keep the user in the exploration loop by developing displays for perceptual data mining. This approach allows a domain expert to search the data for useful relationships and can be effective when automated rules are hard to define. However, designing models of the abstract data and defining appropriate displays are critical tasks in building a useful system. Designing displays of abstract data is especially difficult when multi-sensory interaction is considered. New technology, such as Virtual Environments, enables such multi-sensory interaction. For example, interfaces can be designed that immerse the user in a 3D space and provide visual, auditory and haptic (tactile) feedback. It has been a goal of Virtual Environments to use multi-sensory interaction in an attempt to increase the human-to-computer bandwidth. This approach may assist the user to understand large information spaces and find patterns in them. However, while the motivation is simple enough, actually designing appropriate mappings between the abstract information and the human sensory channels is quite difficult. Designing intuitive multi-sensory displays of abstract data is complex and needs to carefully consider human perceptual capabilities, yet we interact with the real world everyday in a multi-sensory way. Metaphors can describe mappings between the natural world and an abstract information space. This thesis develops a division of the multi-sensory design space called the MS-Taxonomy. The MS-Taxonomy provides a concept map of the design space based on temporal, spatial and direct metaphors. The detailed concepts within the taxonomy allow for discussion of low level design issues. Furthermore the concepts abstract to higher levels, allowing general design issues to be compared and discussed across the different senses. The MS-Taxonomy provides a categorisation of multi-sensory design options. However, to design effective multi-sensory displays requires more than a thorough understanding of design options. It is also useful to have guidelines to follow, and a process to describe the design steps. This thesis uses the structure of the MS-Taxonomy to develop the MS-Guidelines and the MS-Process. The MS-Guidelines capture design recommendations and the problems associated with different design choices. The MS-Process integrates the MS-Guidelines into a methodology for developing and evaluating multi-sensory displays. A detailed case study is used to validate the MS-Taxonomy, the MS-Guidelines and the MS-Process. The case study explores the design of multi-sensory displays within a domain where users wish to explore abstract data for patterns. This area is called Technical Analysis and involves the interpretation of patterns in stock market data. Following the MS-Process and using the MS-Guidelines some new multi-sensory displays are designed for pattern detection in stock market data. The outcome from the case study includes some novel haptic-visual and auditory-visual designs that are prototyped and evaluated.