Handling fuzziness in temporal databases

This paper proposes a new data model, called FuzzTime, which is capable of handling both aspects of fuzziness and time of data. These two features can always be encountered simultaneously in many applications. This work is aimed to be a conceptual framework for advanced applications of database systems. Our approach has extended the concept of the relational data model to have such a capability. The notion of linguistic variables, fuzzy set theory and possibility theory have been employed in handling the fuzziness aspect, and the discrete time model has been assumed. Some important time-related operators to be used in a temporal query evaluation with an existence of fuzziness are also discussed