Research data is being generated and modified at an increasingly accelerated rate. Iterations and derivations are being crafted at an almost equal velocity. With this increase comes a growing need to track the metadata about the data being generated. Where did this dataset originate? What exactly do the column headers mean? Who was the original publisher? Do I have the latest version of the data? This is to only name a few. As data is shared second or third-hand, or via alternative methods such as physical media or cloud based storage mechanisms, the veracity of the implicit metadata becomes circumstantial. This research quantified and contrasted existing file metadata management solutions, showing their inadequacy to solve the above stated problem, and highlighted the need for a new solution. The system subsequently established and developed by this research was designed to allow for arbitrary file metadata definitions across file systems in a collaborative manner, while facilitating platform independence and easy adoption.
|Adviser||James Eric Dietz|
|Subjects||Information science; Computer science|
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