Abstract-Treemaps provide an interesting solution for representing hierarchical data. However, most studies have mainly focused on layout algorithms and paid limited attention to the interaction with treemaps. This makes it difficult to explore large data sets and to get access to details, especially to those related to the leaves of the trees. We propose the notion of zoomable treemaps (ZTMs), an hybridization between treemaps and zoomable user interfaces that facilitates the navigation in large hierarchical data sets. By providing a consistent set of interaction techniques, ZTMs make it possible for users to browse through very large data sets (e.g., 700,000 nodes dispatched amongst 13 levels). These techniques use the structure of the displayed data to guide the interaction and provide a way to improve interactive navigation in treemaps.

Structured graphics models such as Scalable Vector Graphics (SVG) enable designers to create visually rich graphics for user interfaces. Unfortunately current programming tools make it difficult to implement advanced interaction techniques for these interfaces. This paper presents the Hierarchical State Machine Toolkit (HsmTk), a toolkit targeting the development of rich interactions.The key aspect of the toolkit is to consider interactions as firstclass objects and to specify them with hierarchical state machines. This approach makes the resulting behaviors self-contained, easy to reuse and easy to modify. Interactions can be attached to graphical elements without knowing their detailed structure, supporting the parallel refinement of the graphics and the interaction.

We introduce semantic pointing, a novel interaction technique that improves target acquisition in graphical user interfaces (GUIs). Semantic pointing uses two independent sizes for each potential target presented to the user: one size in motor space adapted to its importance for the manipulation, and one size in visual space adapted to the amount of information it conveys. This decoupling between visual and motor size is achieved by changing the control-to-display ratio according to cursor distance to nearby targets. We present a controlled experiment supporting our hypothesis that the performance of semantic pointing is given by Fitts' index of difficulty in motor rather than visual space. We apply semantic pointing to the redesign of traditional GUI widgets by taking advantage of the independent manipulation of motor and visual widget sizes.