Temporal Granularity: Completing the Puzzle

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.

[1]  Albert Croker,et al.  The historical relational data model (HRDM) and algebra based on lifespans , 1986, 1987 IEEE Third International Conference on Data Engineering.

[2]  Nikos A. Lorentzos.  DBMS Support for Nonmetric Systems , 1994 .

[3]  Duane Szafron,et al.  Temporality in object database management systems , 1998 .

[4]  Barbara Pernici,et al.  Time modeling in office information systems , 1985, SIGMOD Conference.

[5]  Curtis E. Dyreson,et al.  A Glossary of Time Granularity Concepts , 1997, Temporal Databases, Dagstuhl.

[6]  Carlo Combi,et al.  GCH-OSQL: a temporally-oriented object-oriented query language based on a three-valued logic , 1997, Proceedings of TIME '97: 4th International Workshop on Temporal Representation and Reasoning.

[7]  Sushil Jajodia,et al.  A general framework for time granularity and its application to temporal reasoning , 1998, Annals of Mathematics and Artificial Intelligence.

[8]  Sushil Jajodia,et al.  Dealing with Granularity of Time in Temporal Databases , 1991, CAiSE.

[9]  Sushil Jajodia,et al.  Temporal modules: an approach toward federated temporal databases , 1993, Inf. Sci..

[10]  Richard T. Snodgrass,et al.  The TSQL2 Temporal Query Language , 1995 .

[11]  Francesco Pinciroli,et al.  Applying object-oriented technologies in modeling and querying temporally oriented clinical databases dealing with temporal granularity and indeterminacy , 1997, IEEE Transactions on Information Technology in Biomedicine.

[12]  Duane Szafron,et al.  Modeling temporal primitives: back to basics , 1997, CIKM '97.

[13]  Luca Chittaro,et al.  Temporal Indeterminancy in Deductive Databases: An Approach Based on Event Calculus , 1997, ARTDB.

[14]  Angelo Montanari,et al.  Dealing with different time granularities in formal specifications of real-time systems , 1991, Real-Time Systems.

[15]  Barbara Pernici,et al.  Automatic deduction of temporal information , 1992, TODS.

[16]  Ramez Elmasri,et al.  The Consensus Glossary of Temporal Database Concepts - February 1998 Version , 1997, Temporal Databases, Dagstuhl.

[17]  Nikos A. Lorentzos.  DBMS Support for Nonmetric Measurement Systems , 1994, IEEE Trans. Knowl. Data Eng..

[18]  Angelo Montanari,et al.  Dealing with Time Granularity in the Event Calculus , 1992, FGCS.

[19]  Duane Szafron,et al.  Modeling Time: Back to Basics , 1996 .

[20]  Jörgen Hansson,et al.  Proceedings of the Second International Workshop on Active, Real-Time, and Temporal Database Systems , 1997 .

[21]  James Clifford,et al.  A Simple, General Structure for Temporal Domains , 1986, Temporal Aspects in Information Systems.

[22]  F Pinciroli,et al.  Managing Different Time Granularities of Clinical Information by an Interval-based Temporal Data Model , 1995, Methods of Information in Medicine.

[23]  Eric J. Topol,et al.  Diagnosing and Managing Unstable Angina, Quick Reference Guide for Clinicians , 1994 .

[24]  C.E. Dyreson,et al.  Valid-time indeterminacy , 1993, Proceedings of IEEE 9th International Conference on Data Engineering.

[25]  Claudio Bettini,et al.  Symbolic representation of user-defined time granularities , 1999, Proceedings. Sixth International Workshop on Temporal Representation and Reasoning. TIME-99.

[26]  Sushil Jajodia,et al.  Logical design for temporal databases with multiple granularities , 1997, TODS.

[27]  Duane Szafron,et al.  An Object-Oriented Framework for Temporal Data Models , 1997, Temporal Databases, Dagstuhl.

[28]  David J. Maguire,et al.  Geographical Information Systems , 1993 .

[29]  John B. Shoven,et al.  I , Edinburgh Medical and Surgical Journal.

[30]  Duane Szafron,et al.  Temporal granularity for unanchored temporal data , 1998, CIKM '98.