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On completeness of historical relational query languages
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Source ACM Transactions on Database Systems (TODS) archive
Volume 19 ,  Issue 1  (March 1994) table of contents
Pages: 64 - 116  
Year of Publication: 1994
ISSN:0362-5915
Authors
James Clifford  New York Univ., New York, NY
Albert Croker  City Univ. of New York, New York, NY
Alexander Tuzhilin  New York Univ., New York, NY
Publisher
ACM  New York, NY, USA
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Downloads (6 Weeks): 3,   Downloads (12 Months): 40,   Citation Count: 19
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ABSTRACT

Numerous proposals for extending the relational data model to incorporate the temporal dimension of data have appeared in the past several years. These proposals have differed considerably in the way that the temporal dimension has been incorporated both into the structure of the extended relations of these temporal models and into the extended relational algebra or calculus that they define. Because of these differences, it has been difficult to compare the proposed models and to make judgments as to which of them might in some sense be equivalent or even better. In this paper we define temporally grouped and temporally ungrouped historical data models and propose two notions of historical relational completeness, analogous to Codd's notion of relational completeness, one for each type of model. We show that the temporally ungrouped models are less expressive than the grouped models, but demonstrate a technique for extending the ungrouped models with a grouping mechanism to capture the additional semantic power of temporal grouping. For the ungrouped models, we define three different languages, a logic with explicit reference to time, a temporal logic, and a temporal algebra, and motivate our choice for the first of these as the basis for completeness for these models. For the grouped models, we define a many-sorted logic with variables over ordinary values, historical values, and times. Finally, we demonstrate the equivalence of this grouped calculus and the ungrouped calculus extended with a grouping mechanism. We believe the classification of historical data models into grouped and ungrouped models provides a useful framework for the comparison of models in the literature, and furthermore, the exposition of equivalent languages for each type provides reasonable standards for common, and minimal, notions of historical relational completeness.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

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CITED BY  19
 
 
 
 
 
 
 
 
 
 
 


REVIEW

"Jaroslav Pokorny : Reviewer"

The authors extend the relational data model to include a temporal dimension. They distinguish between two approaches that have appeared in the literature—temporally grouped (TG) and temporally ungrouped (TU) historical data. They define  more...

Collaborative Colleagues:
James Clifford: colleagues
Albert Croker: colleagues
Alexander Tuzhilin: colleagues

Peer to Peer - Readers of this Article have also read: