The importance of incorporating time in databases has been well realized by the community and time varying databases have been extensively studied by researchers. The main idea is to model up-to-date changes to data since it became available. Time information is mostly overlaid on the traditional databases, and extensional time dimension helps in inquiring or past data / this all becomes possible only once the idea is realized and favored by commercial database management systems. Unfortunately, one disadvantage of the temporal database management system is that it has not been commercialized. Firstly XML ,eXtensible Markup Language, is a defacto standard for data interchange and hence integrating XML as the data model is decided. The motivation for the work described in this thesis is two-fold / transferring databases into XML with changing crisp values into fuzzy variables describing fuzzy sets and second bitemporal databases form one interesting type of temporal databases. Thus, purpose is to suggest a complete automated system that converts any bitemporal database to its fuzzy XML schema definition. However, the implemented temporal database operators are database content independent. Fuzzy elements are capable of having different membership functions and varying number of linguistic variables. A scheme for determining membership function parameters is proposed. Finally, fuzzy queries have also been implemented as part of the system.

This thesis is focused on PostgreSQL database system. You can find here introducing to temporal databases, database system PostgreSQL, proposal of temporal extension for PostgreSQL and implementation chapter with examples of using this extension. In this thesis is also using temporal database systems and use temporal databases in practise.