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Managing Large Volumes of Distributed Scientific Data

Abstract
The ability to store large volumes of data is increasing faster than processing power. Some existing data management methods often result in data loss, inaccessibility or repetition of scientific simulations. We propose a framework which promotes collaboration and simplifies data management. We propose an implementation independent framework to promote collaboration and data management across a distributed environment. The framework features are demonstrated using a .NET Framework implementation called the Storage and Processing Framework.

Keywords

File Object Model, Data management, database

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