Efficient management of large metadata catalogs in a ubiquitous computing environment
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Abstract
Trends in experimental sciences, such as astrophysics, have led to many critically needed, non-normalized, and massive meta-data catalogs that organize collections of recorded photographic and spectrographic observations of similar size. Observations of the night sky can best be presented using a data model that conveys the observations, analysis, objects contained with the observations, and results of analysis pertaining to those objects. Such a model is devised and it is referred to as the internet Flexible Image Transport System (iFITS). In addition a set of mapping functions to transform instances of the Sloan Digital Sky Survey into instances of iFITS, a light-weight marshaling method to transfer data to and from server side instances to mobile instances. Furthermore, this dissertation explores four architectures such as content management, software/ infrastructure/ platform as a service, context rule engine based request-response loop factory, and representational state transfer (REST) based query engines to facilitate the mining of the meta-data catalogs containing these observations.
Embargo status: Restricted until 06/2162. To request the author grant access, click on the PDF link to the left.