Modeling Data Quality with Possibility-distributions

Description of data quality relies heavily on numbers. When dealing with data sets, which have been collected during longer periods, however, variation in the data quality will become evident. Older data may have different quality than newer data and other aspects including height or accessibility may influence the quality of parts of the data set. Precise numbers do not reflect this variation, thus I propose the use of fuzzy numbers to specify data quality. Fuzzy numbers are based on the specification of a distribution function. The distribution function may be a probability or a possibility function. Probability is more difficult to determine than possibility. Still, the possibility function may provide all information relevant for the user. Thus, providing the possibility function may be sufficient to improve the data quality description. The paper uses the Austrian cadastre as an example. The separation between legal and technical influences allows the specification of the possibility distributions. The example is restricted to temporal and positional accuracy and completeness. The assumption of quality requirements of two user groups finally allows assessing the fitness for use based on the possibility distributions.