Multi-Aspect Evaluation of Data Quality in Scientific Databases


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Date: January 2008
Type: White Paper
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Overview: This paper from Institute of Biocybernetics and Biomedical Engineering presents a method of multi-aspect data quality evaluation. The data can be evaluated from the points of view of their actuality, relevance, accuracy, credibility, irredundancy, completeness, legibility, etc. The quality factors can be extended on higher-order data structures. Vector representing the data structures’ qualities can be compared and the best data structures can be chosen using the concept of semi-ordering of a linear vector space introduced by Kantorovitsch. The way of using this concept to data evaluation is described.

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