Michael Rooke, Tovi Grossman, George Fitzmaurice
Michael Rooke, Tovi Grossman, George Fitzmaurice
Graphics Interface Conference
2011
AppMap: Exploring User Interface Visualizations (3:46 min.)
In traditional graphical user interfaces, the majority of UI elements are hidden to the user in the default view. Application designers and users desire more space for their application data and thus want to minimize the user interface footprint. We explore the benefits of dedicating additional screen space for presenting an alternative visualization of an application’s user interface. Some potential benefits are to assist users in examining complex software, understanding the extent of an application’s capabilities, and exploring the available features. Thus, we propose user interface visualizations, alternative representations of an application’s interface augmented with usage information. We first introduce a design space for UI visualizations and describe some initial prototypes and insights based on this design space. We then present AppMap, our new design, which displays the entire function set of AutoCAD and allows the user to interactively explore the visualization which is augmented with visual overlays displaying analytical data about the functions and their relations. In our initial studies, users welcomed this new presentation of functionality, and the unique information that it presents. We conclude by summarizing some potential benefits of UI visualizations.
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Visual data representations leverage the power of human perception to process complex information, and through interaction, garner new insights. Our research focuses on visualizing data from a wide variety of domains and fundamentally tackles the question, what makes a visualization effective? We explore novel visual encodings and interaction techniques, multiscale approaches, and even simulation to bridge human and automated analysis of multivariate, time-series, and graph data, ultimately aiding in hypothesis generation, testing, and sense making.
The Learning project aims to investigate advanced techniques for assisting users in learning complicated applications. We are interested in a range of investigations from the scientific study of the human learning process to prototyping novel interaction techniques for improving the general learning mechanisms that can be applied to all applications.