Abstract
In the last two decades, the relational data model has gained popularity because of its simplicity and solid mathematical foundation. However, the relational data model does not address the temporal dimension of data. Variation of data over time is treated in the same way as ordinary data. In fact, most applications require temporal data to certain extent. Hence, the concept of temporal database is coined. In the design of relational or temporal data bases, normal forms play central role. Several normal forms for temporal relational databases have been proposed previously. But the order of application of these temporal normal forms and the relations among them is not explicit. The role played by temporal normal forms during temporal data base design, closely parallels that of normal forms during conventional data base design. In this paper, it is shown that how temporal normal forms, including the related concepts of temporal dependencies and temporal keys may be used so that temporal database can be designed in an efficient manner.
Additional information
Notes on contributors
P V Kumar
P V Kumar, is working as Associate Professor in the Department of Computer Science & Engineering, Osmania University, Hyderabad. He did MSc (Stat) and MTech (CSE) from Osmania University. He has got three years of industrial experience. He started his teaching profession in the year 1987. He guided many BE, MCA and MTech students. He presented three papers in various international conferences. He acted as Chairman, BOS in CSE, OU during 1997–99. His research interests include Data Base Management Systems and Knowledge Discovery.
C Raghavendra Rao
C R Rao, is working as Reader in the Department of Mathematics and Statistics, School of Mathematics and Computer Information Sciences, University of Hyderabad. He did MSc (Stat) and MTech (CSE) and PhD from Osmania University, Hyderabad. He started his teaching profession in the year 1984. He is a co-author of a book ‘Evaluation of Total Literacy Campaigns’ and four projects are to his credit. His research interests include Operation Research and Knowledge Discovery.