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Metadata-Driven Management of Scientific Data

Metadata-Driven Management of Scientific Data By Aman Kumar, Sponsored by The Ohio State Medical Center

Management of large amounts of complex and multi-dimensional scientific data, residing in different data sources has become a huge challenge in the scientific domain. Researchers require technologies to facilitate understanding of the data, in particular the ability to effectively organize complex data, perform efficient analysis, share and discover relevant data and facilitate searches over large data sets. Existing systems and approaches have tried to resolve these problems individually and have been successful to some extent. But there is a lack of an end-to-end solution that suits the dynamically emerging needs of the scientific community. This thesis is an attempt to fill this gap by presenting the work done in each of these areas and by proposing an end-to-end framework that follows the meta-data driven approach to resolve these issues in an integrated manner. Also, the framework demonstrates that the concept of ontologies and folksonomies can be leveraged to manage scientific data. To provide validation to the framework, the component architecture and functionality of its simple yet powerful implementation, MetaDB is described. Click here for poster

Student: Aman Kumar

Sponsored by The Ohio State Medical Center

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