An intensional approach for periodic data in relational databases

  • Authors:

  • Paolo Terenziani;Bela Stantic;Alessio Bottrighi;Abdul Sattar

  • Affiliations:

  • DISIT, Computer Science Institute, University of Piemonte Orientale, Alessandria, Italy;Institute for Integrated and Intelligent Systems Griffith University, Brisbane, Australia;DISIT, Computer Science Institute, University of Piemonte Orientale, Alessandria, Italy;Institute for Integrated and Intelligent Systems Griffith University, Brisbane, Australia

  • Venue:
  • Journal of Intelligent Information Systems
  • Year:
  • 2013

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Abstract

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.