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Quality of data plays a very important role in any scientific research. In this paper the authors present some of the challenges that they face in managing and maintaining data quality for a terabyte scale biometrics repository. They have developed a step by step model to capture, ingest, validate, and prepare data for biometrics research. During these processes, there are many hidden errors which can be introduced into the data. Those errors can affect the overall quality of data, and thus can skew the results of biometrics research.
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