A Flexible, Low-Complexity Device Adaptation Approach For Data Presentation

Visual data presentations require adaptation for appropriate display on a viewing device that is limited in resources such as computing power, screen estate, and/or bandwidth. Due to the complexity of suitable adaptation, the few proposed solutions available are either too resource-intensive or inflexible to be applied broadly. Effective use and acceptance of data visualization on constrained viewing devices require adaptation approaches that are tailored to the requirements of the user and the capabilities of the viewing device.We propose a predictive device adaptation approach that takes advantage of progressive data refinement. The approach relies on hierarchical data structures that are created once and used multiple times. By incrementally reconstructing the visual presentation on the client with increasing levels of detail and resource utilization, we can determine when to truncate the refinement of detail so as to use the resources of the device to their full capacities. To determine when to finish the refinement for a particular device, we introduce a profile-based strategy which also considers user preferences. We discuss the whole adaptation process from the storage of the data into a scalable structure to the presentation on the respective viewing device. This particular implementation is shown for two common data visualization methods, and empirical results we obtained from our experiments are presented and discussed.