Data management techniques for unmanaged data

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The growing number of computer users, increasing amount of data, and proliferating data usage styles yield data that does not fit well within traditional data management solutions. My research hypothesis is that as the number of computer users grow, there will be ever more of this data to be managed. My objective is to use traditional data management techniques to harness this unmanaged data, particularly heterogeneous data used by many parties. In particular, I seek to (1) enable users to better understand their data when it is managed inside a system that is not of their design, whether it is a conglomeration of disparate data from many sources, or their own data stored in a different data model and (2) enable integration of data from multiple non-traditional data sources (e.g., Computer Aided Design (CAD) or Geographic Information Systems (GIS) data).