Visualizing and analyzing human-centered data streams

Abstract

The mainstream population is readily adapting to the notion that the carrying of mobile computational devices such as cell phones and PDAs on one's person is as essential as taking along one's watch or credit cards. In addition to their stated and oftentimes proprietary functionality, these technological innovations have the potential to also function as powerful sensory data collectors. These devices are able to record and store a variety of data about their owner's everyday activities, a new development that may significantly impact the way we recall information. Human memory, with its limitations and subjective recall of events, may now be supplemented by the latent potential of these in-place devices to accurately record one's daily activities, thereby giving us access to a wealth of information about our own lives. In order to make use of this recorded information, it must be presented in an easily understood format: timelines have been a traditional display metaphor for this type of data. This thesis explores the visualization and navigation schemes available for these large temporal data sets, and the types of analyzation that they facilitate.