Patina: Smart Heatmaps for Visualizing Application Usage (2:57 min.)
Video title (x:xx min.)
We present Patina, an application independent system for collecting and visualizing application usage data which requires no instrumentation of the target application for either the data collection or presentation. All data collected through standard window metrics and accessibility APIs. The primary visualization is a smart heatmap overly which is dynamically created to match the content and location of the user interface controls visible in the active application even if the controls change location or shape. After reviewing the design goals, we explain the implementation of both the data collection and presentation parts of the system. Lastly, we explore three additional application of the Patina system based on previous research and report on an internal usage evaluation.
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.