Using and Collecting Annotated Behavioral Trace Data For Designing and Developing Context-Aware Application.

context-aware application development;capture and playback;design process and toolkit;collecting annotated behavioral data;mobile crowdsourcing;mobile interruptibility and receptivity;Information and Library Science;Social Sciences;Information

Chang, Yung-JuKlasnja, Predrag ;

University of Michigan

关键词: context-aware application development;    capture and playback;    design process and toolkit;    collecting annotated behavioral data;    mobile crowdsourcing;    mobile interruptibility and receptivity;    Information and Library Science;    Social Sciences;    Information;   

Others  :  https://deepblue.lib.umich.edu/bitstream/handle/2027.42/120705/yuchang_1.pdf?sequence=1&isAllowed=y

瑞士|英语

来源: The Illinois Digital Environment for Access to Learning and Scholarship

【 摘 要 】

Ubiquitous Computing has been a focus of numerous researchers hoping to create environments where users are served by heterogeneous computing devices responding to their contexts. Thanks to these researchers;; research efforts, computing infrastructures, sensing devices, and intelligent systems have been developed, making the creation of context-aware systems more viable, economic, and appealing to designers and developers. This thesis aims to respond to this emerging trend by developing systems and practices supporting more effective development of context-aware applications. In particular, I focus on using a capture-and-playback approach—capturing and playing back behavioral and contextual data to prototype, test, and evaluate context-aware applications. The thesis makes five main contributions in this area. The first two contributions focus on supporting playback. In Chapter 3, I present findings and lessons learned from two case studies and a developer study involving the capture-and-playback approach and tool, of which the results inform the design space for supporting context-aware application development. Second, I present a design, development, and evaluation of a capture-and-playback toolset called CaPla, which support different activities in developing context-aware applications.Starting from Chapter 4, 5, and 6. I present my research efforts making three contributions to data capture. First, I present findings from an empirical study investigating smartphone users’ mobile receptivity to incoming communications. The findings indicate factors to be considered when sending data capture requests to smartphone users. In Chapter 5, I present a field study investigating the effectiveness of using three different approaches for collecting personal behavioral and contextual data. The results show pros and cons of the three approaches, as well as smartphone users’ behaviors in using the approaches and how activity impacts users’ data collection behaviors. Finally, in Chapter 6, I present a configurable, flexible, and extensible mobile data collection tool called Minuku. Minuku can monitor complex contextual conditions, schedule and perform highly situated actions, and allows performing different styles of data collection approaches.The findings of the studies and the experiences with the systems point towards the design space for a more comprehensive capture-and-playback tool and a set of practices of performing a capture-and-playback approach.