Attribute-based data quality evaluation in regional Material Flow Analysis

Abstract

A method for data quality evaluation in macro scale MFAs such as national resource budgets is presented. MFA data is never totally accurate but may have certain defects. The four information defects semantic, representativeness, provenance and context are introduced. These information defects are considered to be functions of data attributes. Data attributes are assigned to MFA data according to an existing framework. A method for quantification of information defects and for expressing the data quality of a flow by a single number is presented. It provides opportunities for understanding and evaluating resource budgets, their a priori information basis and their information content.