关键词: 数据质量, 信息论, 信息熵

Abstract: To automatically quantify data quality dimensions in multiple-source environment，it proposes a novel approach to automatically Quantify Dimensions within Context（QDC）.Data quality can be gauged by discrepancy between data view and its entity’s perfect representation.Since it is difficult to obtain the perfect representation of entity，it proposes to approximate the perfect representation within its available context and quality dimensions can be quantified in this context scope.By naturally borrowing entropy concepts from information theory，the measurement is easily given for different types of data.In this way，the two most important quality dimensions，that are accuracy and completeness，are properly quantified.This QDC approach can not only give an objective score and ranking in a cooperative multi-source environment but also avoid human’s laborious interaction.As an automatic quality rating solution this approach is distinguished，especially for large scale datasets.Theory and experiment shows the approach performs well for quality rating.

Key words: data quality, information theory, entropy