Handheld displays enable flexible spatial exploration of information spaces -- users can physically navigate through three-dimensional space to access information at specific locations. Having users constantly hold the display, however, has several limitations: (1) inaccuracies due to natural hand tremors; (2) fatigue over time; and (3) limited exploration within arm's reach. We investigate autonomous, self-actuated displays that can freely move and hold their position and orientation in space without users having to hold them at all times. We illustrate various stages of such a display's autonomy ranging from manual to fully autonomous, which -- depending on the tasks -- facilitate the interaction. Further, we discuss possible motion control mechanisms for these displays and present several interaction techniques enabled by such displays. Our Hover Pad toolkit enables exploring five degrees of freedom of self-actuated and autonomous displays and the developed control and interaction techniques. We illustrate the utility of our toolkit with five prototype applications, such as a volumetric medical data explorer.

In application domains like healthcare, psychology and e-learning, data collection is based on specifically tailored paper & pencil questionnaires. Usually, such a paper-based data collection is accomplished by a massive workload regarding the processing, analysis, and evaluation of the data collected. To relieve domain experts from these manual tasks and to increase the efficiency of the data collection process, we developed a generic approach for realizing process-driven smart mobile device applications based on process management technology. According to this approach, the logic of a questionnaire is described in terms of an explicit process model whose enactment is driven by a generic process engine. Our goal is to demonstrate that such a process-aware design of mobile business applications is useful with respect to mobile data collection. Hence, we developed a generic architecture comprising the main components of mobile data collection applications. Furthermore, we used these components for developing mobile electronic questionnaires for psychological studies. The paper presents the challenges identified in this context and discusses the lessons learned. Overall, process management technology offers promising perspectives for developing mobile business applications at a high level of abstraction.