A Study on Temporal Data Models and Aggregate Functions 


Vol. 4,  No. 12, pp. 2947-2959, Dec.  1997
10.3745/KIPSTE.1997.4.12.2947


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  Abstract

Temporal data model is able to handle the time varying information, which is to add temporal attributes to conventional data model. The temporal data model is classified into three models depending upon supporting time dimension, that are the valid time model to support valid time, the transaction time model to support transaction model, and the bitemporal data model to support valid time and transaction time. Most temporal data models are designed to process the temporal data by extending the relational model. There are two types of temporal data model, which are the tuple timestamping and the attribute timestamping depending on time dimension. In this research, a concept of temporal data model, the time dimension, types of the data model, and a consideration for the data model design are discussed. Also, temporal data models in terms of the time dimension are compared. And the aggregate function model of valid time model is proposed, and then logical analysis for its computing consts has been done.

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[IEEE Style]

L. I. Hong, M. H. Jin, C. D. Young, L. W. Kwon, C. H. Joon, "A Study on Temporal Data Models and Aggregate Functions," The Transactions of the Korea Information Processing Society (1994 ~ 2000), vol. 4, no. 12, pp. 2947-2959, 1997. DOI: 10.3745/KIPSTE.1997.4.12.2947.

[ACM Style]

Lee In Hong, Moon Hong Jin, Cho Dong Young, Lee Wan Kwon, and Cho Hyun Joon. 1997. A Study on Temporal Data Models and Aggregate Functions. The Transactions of the Korea Information Processing Society (1994 ~ 2000), 4, 12, (1997), 2947-2959. DOI: 10.3745/KIPSTE.1997.4.12.2947.

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