An Algebraic Representation of Calendars

This paper uses an algebraic approach to define temporal granularities and calendars. All the granularities in a calendar are expressed as algebraic expressions based on a single “bottom” granularity. The operations used in the algebra directly reflect the ways with which people construct new granularities from existing ones, and hence yield more natural and compact granularities definitions. Calendar is formalized on the basis of the algebraic operations, and properties of calendars are studied. As a step towards practical applications, the paper also presents algorithms for granule conversions between granularities in a calendar.

[1]  Lin Hong EFFICIENT CONVERSION BETWEEN TEMPORAL GRANULARITIES , 1997 .

[2]  Nikos A. Lorentzos,et al.  DBMS support for time and totally ordered compound data types , 1992, Inf. Syst..

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

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

[5]  Christian S. Jensen,et al.  Temporal Databases: Research and Practice , 1998, Lecture Notes in Computer Science.

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

[7]  Michael Stonebraker,et al.  Implementing calendars and temporal rules in next generation databases , 1994, Proceedings of 1994 IEEE 10th International Conference on Data Engineering.

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

[9]  Michael H. Böhlen,et al.  Efficiently Supporting Temporal Granularities , 1998 .

[10]  Sushil Jajodia,et al.  Temporal Databases: Research and Practice , 1998 .

[11]  Claudio Bettini,et al.  Symbolic representation of user-defined time granularities , 2004, Annals of Mathematics and Artificial Intelligence.

[12]  David Forster,et al.  A Representation for Collections of Temporal Intervals , 1986, AAAI.

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

[14]  Curtis E. Dyreson,et al.  Efficiently Supported Temporal Granularities , 2000, IEEE Trans. Knowl. Data Eng..

[15]  Sushil Jajodia,et al.  Time Granularities in Databases, Data Mining, and Temporal Reasoning , 2000, Springer Berlin Heidelberg.

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

[17]  Ramez Elmasri,et al.  Specification of Calendars and Time Series for Temporal Databases , 1996, ER.

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

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

[20]  Thomas Dean,et al.  Using temporal hierarchies to efficiently maintain large temporal databases , 1989, JACM.