Efficient Management of Large Metadata Catalogs in a Ubiquitous Computing Environment

Trends in experimental sciences such as astrophysics have led to many critically needed non-normalized and massive metadata 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 proposed 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 lightweight 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 metadata catalogs containing these observations.