An intensional approach for periodic data in relational databases

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Author(s)
Terenziani, Paolo
Stantic, Bela
Bottrighi, Alessio
Sattar, Abdul
Year published
2013
Metadata
Show full item recordAbstract
Periodic data play a major role in many application domains, spanning from manufacturing to office automation, from scheduling to data broadcasting. In many of such domains, the huge number of repetitions make the goal of extesionally storing and accessing such data very challenging. In this paper, we propose a new methodology, based on an intensional representation of periodic data. The representation model we propose captures the notion of periodic granularity provided by the temporal database glossary, and is an extension of the TSQL2 temporal relational data model. We define the algebraic operators, and introduce ...
View more >Periodic data play a major role in many application domains, spanning from manufacturing to office automation, from scheduling to data broadcasting. In many of such domains, the huge number of repetitions make the goal of extesionally storing and accessing such data very challenging. In this paper, we propose a new methodology, based on an intensional representation of periodic data. The representation model we propose captures the notion of periodic granularity provided by the temporal database glossary, and is an extension of the TSQL2 temporal relational data model. We define the algebraic operators, and introduce access algorithms to cope with them, proving that they are correct with respect to the traditional extesional approach.We also provide an experimental evaluation of our approach.
View less >
View more >Periodic data play a major role in many application domains, spanning from manufacturing to office automation, from scheduling to data broadcasting. In many of such domains, the huge number of repetitions make the goal of extesionally storing and accessing such data very challenging. In this paper, we propose a new methodology, based on an intensional representation of periodic data. The representation model we propose captures the notion of periodic granularity provided by the temporal database glossary, and is an extension of the TSQL2 temporal relational data model. We define the algebraic operators, and introduce access algorithms to cope with them, proving that they are correct with respect to the traditional extesional approach.We also provide an experimental evaluation of our approach.
View less >
Journal Title
Journal of Intelligent Information Systems
Volume
41
Issue
2
Copyright Statement
© 2013 Springer Netherlands. This is the author-manuscript version of this paper. Reproduced in accordance with the copyright policy of the publisher. The original publication is available at www.springerlink.com.
Subject
Data management and data science
Data structures and algorithms
Information and computing sciences