A Taxonomy of Integration Techniques for Spatial and Non-Spatial Visualizations

Research on visual data representations is traditionally classified into methods assuming an inherent mapping from data values to spatial coordinates (scientific visualization and real-time rendering) and methods for abstract data lacking explicit spatial references (information visualization). In practice, however, many applications need to analyze data comprising abstract and spatial information, thereby spanning both visualization domains. Traditional classification schemes do not support a formal description of these integrated systems. The contribution of this paper is a taxonomy that describes a holistic design space for integrating components of spatial and abstract visualizations. We structure a visualization into three components: Data, Visual, and Navigation. These components can be linked to build integrated visualizations. Our taxonomy provides an alternative view on the field of visualization in a time where the border between scientific and information visualization becomes blurred.