|
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.
 |
1
|
|
 |
2
|
|
| |
3
|
ARIAV, G., AND CLIFFORD, J. 1986 Temporal data management: Models and systems. In New Dzrectwns for Database Systems, G. Ariav and J. Clifford, Eds. Ablex, Norwood, N.J, pp. 168 185.
|
| |
4
|
BANCILHfON, F. 1978. On the completeness of query languages for relational databases. In Proceedings of the 7th Symposium on Mathematical Foundations of Computing. Springer- Verlag, New York, pp. 112-123.
|
 |
5
|
Jay Banerjee , Won Kim , Hyoung-Joo Kim , Henry F. Korth, Semantics and implementation of schema evolution in object-oriented databases, Proceedings of the 1987 ACM SIGMOD international conference on Management of data, p.311-322, May 27-29, 1987, San Francisco, California, United States
|
| |
6
|
|
| |
7
|
CHANDRA, A. K, AND HAREL, D 1980. Computable queries for relational data bases J. Comput Syst. Sci. 21, 2 (Oct.), 156-178.
|
| |
8
|
CLIFFORD, J. 1982. A model fbr historical databases. In Proceedzngs of Workshop on Logical Bases for Data Bases (Toulouse, France, Dec.), ONERA-CERT, Toulouse, France.
|
| |
9
|
|
| |
10
|
|
 |
11
|
|
 |
12
|
|
| |
13
|
CODD, E F. 1972 Relahonal completeness of data base sublanguages. In Data Base Systems, R. Rustin, Ed. Prentice-Hall, Englewood Cliffs, N.J.
|
| |
14
|
|
| |
15
|
ENDERTON, H.B. 1972. A Mathematical Introductwn to Logic. Academic Press, New York.
|
| |
16
|
FISCHER, P. C., AND VAN GUCHT, D. 1985 Determining when a structure is a nested relation. In Ii~ternatzonal Conference on Very Large Databases. pp. 171-180.
|
| |
17
|
|
| |
18
|
|
 |
19
|
|
| |
20
|
HALL, P., OWLETT, J., AND TODD, S. J.P. 1976. Relations and entitles In Modelling in Data Base Management Systems, G. M. Nijssen, Ed. North-Holland, Amsterdam.
|
| |
21
|
HALMOS, P. 1960. Naive Set Theory. Van Nostrand, Princeton, N.J.
|
| |
22
|
JONES, S., AND MASON, P.J. 1980. Handling the time dimension in a data base. In Proceedings of the International Conference of Data Bases (Heyden, U.K., July). British Computer Society, London, pp. 65-83.
|
 |
23
|
F. Kabanza , J.-M. Stevenne , P. Wolper, Handling infinite temporal data, Proceedings of the ninth ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems, p.392-403, April 02-04, 1990, Nashville, Tennessee, United States
[doi> 10.1145/298514.298590]
|
| |
24
|
KAMP, H. 1971. Formal properties of'now'. Theoria 37, 3, 227 273.
|
| |
25
|
KAMP, H. 1968. On the tense logic and the theory of order. Ph.D. thesis, Philosophy Dept., Univ. of California at Los Angeles.
|
 |
26
|
|
| |
27
|
|
| |
28
|
LORENTZOS, R. G., aND JOHNSON, N.A. 1987. TRA: A model for a temporal relational algebra. In Proceedings of the Conference on Temporal Aspects in Informatzon Systems. AFCET, pp. 99-112.
|
| |
29
|
|
| |
30
|
MCI~zNZIE, E. 1986. Bibliography: Temporal databases. ACM SIGMOD Rec. 15, 4 (Dec.), 40-52.
|
| |
31
|
|
| |
32
|
McKENzm, E., AND SNODGRASS, R. 1991b. Supporting valid time in an historical relational algebra: Proofs and extensions. Tech. Rep. TR-91-15, Dept. of Computer Science, Univ. of Arizona, Tucson, Aug.
|
 |
33
|
|
| |
34
|
|
| |
35
|
QUINE, W. V.O. 1953. From a Logical Poilzt of Vtew. Harvard University Press, Cambridge, Mass.
|
| |
36
|
RESCHER, N., aND URQUHART, A. 1971. Temporal Logic. Springer-Verlag, New York.
|
 |
37
|
|
| |
38
|
|
 |
39
|
|
 |
40
|
|
 |
41
|
|
 |
42
|
|
| |
43
|
SNODGRASS, R., GOMEZ, S., aND MCKENzIE, E. 1989. Aggregates in the temporal query language tquel. Tech. Rep. TR-89-26, Dept. of Computer Science, Univ. of Arizona, Tucson, Nov.
|
 |
44
|
|
| |
45
|
STAM, R., AND SNODGRASS, R. 1988. A bibliography on temporal databases. Database Eng. 7, 4 (Dec.), 231-239.
|
 |
46
|
|
 |
47
|
|
| |
48
|
TANSEL, A., CLIFFORD, J., GADIA, S., JAJODIA, S., SEGEV, A., AND SNODGRASS, R. EDS. 1993. Temporal Databases. Benjamin/Cummings, Menlo Park, Calif.
|
| |
49
|
|
| |
50
|
|
| |
51
|
|
| |
52
|
|
| |
53
|
VAN BENTHEM, J. F A.K. 1983. The Logic of Time. Reidel, Hingham, Mass.
|
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...
Peer to Peer - Readers of this Article have also read:
-
Data structures for quadtree approximation and compression
Communications of the ACM
28, 9
Hanan Samet
-
A hierarchical single-key-lock access control using the Chinese remainder theorem
Proceedings of the 1992 ACM/SIGAPP Symposium on Applied computing
Kim S. Lee
, Huizhu Lu
, D. D. Fisher
-
The GemStone object database management system
Communications of the ACM
34, 10
Paul Butterworth
, Allen Otis
, Jacob Stein
-
Putting innovation to work: adoption strategies for multimedia communication systems
Communications of the ACM
34, 12
Ellen Francik
, Susan Ehrlich Rudman
, Donna Cooper
, Stephen Levine
-
An intelligent component database for behavioral synthesis
Proceedings of the 27th ACM/IEEE conference on Design automation
Gwo-Dong Chen
, Daniel D. Gajski
|