Temporal Granularity: Completing the Puzzle

  • Authors:

  • Iqbal A. Goralwalla;Yuri Leontiev;M. Tamer Özsu;Duane Szafron;Carlo Combi

  • Affiliations:

  • Laboratory for Database Systems Research, Department of Computing Science, University of Alberta, Edmonton, Alberta, Canada T6G 2H1. iqbal@cs.ualberta.ca;Laboratory for Database Systems Research, Department of Computing Science, University of Alberta, Edmonton, Alberta, Canada T6G 2H1. yuri@cs.ualberta.ca;Laboratory for Database Systems Research, Department of Computing Science, University of Alberta, Edmonton, Alberta, Canada T6G 2H1. ozsu@cs.ualberta.ca;Laboratory for Database Systems Research, Department of Computing Science, University of Alberta, Edmonton, Alberta, Canada T6G 2H1. duane@cs.ualberta.ca;Laboratory of Database and Multimedia Systems, Department of Mathematics and Computer Science, University of Udine, via delle Scienze 206, 33100 Udine, Italy. combi@dimi.uniud.it

  • Venue:
  • Journal of Intelligent Information Systems
  • Year:
  • 2001

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Abstract

Granularity is an integral feature of both anchored (e.g., 25 October 1995, July 1996) and unanchored (e.g., 3 minutes, 6 hours 20 minutes, 5 days) temporal data. In supporting temporal data that is specified in different granularities, numerous approaches have been proposed to deal with the issues of converting temporal data from one granularity to another. The emphasis, however, has only been on granularity conversions with respect to anchored temporal data. In this paper we provide a novel approach to the treatment of granularity in temporal data. A granularity is modeled as a special kind of unanchored temporal primitive that can be used as a unit of time. That is, a granularity is modeled as a unit unanchored temporal primitive. We show how unanchored temporal data is represented, give procedures for converting the data to a given granularity, provide canonical forms for the data, and describe how operations between the data are performed. We also show how anchored temporal data is represented at different granularities and give the semantics of operations on anchored temporal data.