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    Documenting and Understanding Everyday Activities through the Selective Archiving of Live Experiences

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    Date
    2007-05-18
    Author
    Hayes, Gillian Rachael
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    Abstract
    This research focuses on the development and study of socially appropriate ways to archive data about important life experiences during unexpected and unstructured situations. This work involves three significant phases: formative studies to understand the data capture needs of particular populations of users in these situations; design and development of a technical architecture for capture and access in these settings coupled with design and development of applications for two specific domain problems; and evaluation of this solution as it pertains to these domain problems. The underlying solution presented in this dissertation is known as selective archiving, in which services are always on and available for recording but require some explicit action to archive data. If no such action is taken, recorded data is deleted automatically after a specified time. Selectively archived segments of data can provide an efficient way to recover and to analyze high quality data that traditionally available. The projects presented in this dissertation provide insight about the ways in which we can support record-keeping in informal and unstructured settings. Furthermore, when examined together, these projects provide a view into the larger generalized problem of unstructured capture and access and the acceptability of capture technologies. These considerations evolved into a set of seven tensions surrounding recording technologies that are presented in this dissertation. Furthermore, the experiences surrounding the deployment and evaluation of selective archiving technologies demonstrate the ways in which people use different types of knowledge and cues from the world to determine their reactions to and adoption of such technologies.
    URI
    http://hdl.handle.net/1853/16222
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    • College of Computing Theses and Dissertations [1156]
    • Georgia Tech Theses and Dissertations [23406]

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