Fuzzy Logic in Data Modeling

This text addresses fundamental issues of fuzzy data modelling, such as fuzzy data representation, fuzzy integrity constraints, fuzzy conceptual modelling, and fuzzy database design. The purpose of introducing fuzzy logic in data modelling is to enhance the classical models such that uncertain and imprecise information can be represented and manipulated. Fuzzy data representation reflects how, where and to what extent fuzziness is incorporated into classical models. Fuzzy integrity constraints are a sort of fuzziness-involved business rules and semantic restrictions that need to be specified and enforced. Fuzzy conceptual modelling describes and treats high-level data concepts and related semantics in a fuzzy context, allowing the model to tolerate imprecision at different degrees. Fuzzy database design provides guidelines for how relation schemes of fuzzy databases should be formed and develops remedies to possible problems of data redundancy and update anomalies.