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For the past two years at USC's Information Laboratory, we have been designing and developing several tools and components to support the underlying database requirements of GENESIS. The Web Services project is the extension of the past work and is aimed to provide the GPS occulation data in shape of web services, clients of which can be integrated in existing and new applications both at JPL and at USC for research purposes. This overall concept here is to create WSDL interfaces and then to pull the data from these interface into any application which requires this data. This architecture shall maximize the potential of reuse, reduce the connections among independent systems and would be accessible from anywhere using any technology. It shall also speed up the development process of new applications which can use already developed and deployed webservice modules.

Presently we have created six web services which return data in different formats mainly XML . These services response to any query submitted for any of the four GPS occulation databases being maintained at USC. The details of these web services can be reached in demo page. Corrosponding to each of these web services, we have also developed web service clients .These clients include Canned query client which provides the user with the option to make a selection from canned queries.The user can also write and save his own queries on the canned query page .Another web client requests meta data from a web service, the purpose of which is to inform the user about the schema of the databases inorder to facilitate the formulation of queries.Details about web service clients can be seen on web pages accessible from WS Clients menu.
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Research Agenda
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Modern data analysis systems need to perform complex statistical queries on very large multidimensional datasets; thus, a number of multivariate statistical methods must be supported. On top of that, the desired accuracy varies per application, user and/or dataset and it can well be traded-off for faster response time. These characteristics lead us to believe that the wavelet transform, with its inherent multiresolution property, will become a likely tool for future database query processing. We are building a general system that utilizes the wavelet decomposition of multidimensional data to not only enhance answering aggregate queries but also to be able to facilitate data-mining functionalities.
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