An efficient approach for modeling temporal database with interval-based timestamping in conventional database management systems

Attaching Date and Time to varying data plays a definite role in representing a dynamic domain and resources on the database systems. The conventional database stores current data and can only represent the knowledge in static sense. Time-varying data representations in relational framework are well described in literature. In this paper we propose an approach for modeling First Normal Form (1NF) and interval-based temporal database over conventional Database Management Systems (DBMS). We choose 1NF approach with interval-based temporal data model for the easily implementation in relational framework as well as to provide the proposed temporal data representation with the modeling and querying power of 1NF relational data model