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Temporal Semantic Assumptions and Their Use in Databases
March/April 1998 (vol. 10 no. 2)
pp. 277-296

Abstract—Data explicitly stored in a temporal database are often associated with certain semantic assumptions. Each assumption can be viewed as a way of deriving implicit information from explicitly stored data. Rather than leaving the task of deriving (possibly infinite) implicit data to application programs, as is the case currently, it is desirable that this be handled by the database management system. To achieve this, this paper formalizes and studies two types of semantic assumptions: point-based and interval-based. The point-based assumptions include those assumptions that use interpolation methods over values at different time instants, while the interval-based assumptions include those that involve the conversion of values across different time granularities. The paper presents techniques on: 1) how assumptions on specific sets of attributes can be automatically derived from the specification of interpolation and conversion functions, and 2) given the representation of assumptions, how a user query can be converted into a system query such that the answer of this system query over the explicit data is the same as that of the user query over the explicit and the implicit data. To precisely illustrate concepts and algorithms, the paper uses a logic-based abstract query language. The paper also shows how the same concepts can be applied to concrete temporal query languages.

[1] J.F. Allen, H. Kautz, R. Pelavin, and J. Tenenberg, Reasoning About Plans, Morgan-Kaufman, 1991.
[2] I. Androutsopoulos, G.D. Ritchie, and P. Thanisch, "Experience Using TSQL2 in a Natural Language Interface," J. Clifford and A. Tuzhilin, eds., Proc. Int'l Workshop Temporal Databases, Recent Advances in Temporal Databases, pp. 113-132,Zurich, Switzerland, 1995.
[3] C. Bettini, X. Wang, E. Bertino, and S. Jajodia, "Semantic Assumptions and Query Evaluation in Temporal Databases," Proc. ACM SIGMOD '95, pp. 257-268,San Jose, Calif., 1995.
[4] C. Bettini, X. Wang, and S. Jajodia, "A General Framework for Time Granularity and Its Application to Temporal Reasoning," Annals of Math. and Artificial Intelligence, vol. 22, nos. 1-2, pp. 29-58, 1998.
[5] J. Chomicki, "History-Less Checking of Dynamic Integrity Constraints," F. Golshani, ed., Proc. Int'l Conf. Data Eng., vol. 8, pp. 557-564, IEEE CSPress, Los Alamitos, Calif., Feb. 1992.
[6] J. Chomicki, Temporal Query Languages: A Survey Proc. Temporal Logic, First Int'l Conf., D.M. Gabbay and H.J. Ohlbach, eds., pp. 506-534, 1994.
[7] J. Clifford and T. Isakowitz, "On the Semantics of (Bi)Temporal Variable Databases," M. Jarke, J. Bubenko, and K. Jeffery, eds., Proc. Fourth Int'l Conf. Extending Database Technology, pp. 215-230, Mar. 1994.
[8] J. Clifford and A. Tansel, "On an Algebra for Historical Relational Databases: Two Views," Proc. ACM SIGMOD Conf., 1985.
[9] J. Clifford and D.S. Warren, "Formal Semantics for Time in Databases," ACM Trans. Database Systems, vol. 8, no. 2, pp. 214-254, June 1983.
[10] T. Dean and D.V. McDermott, "Temporal Data Base Management," Artificial Intelligence J., vol. 32, pp. 1-55, 1987.
[11] M. Escobar-Molano, R. Hull, and D. Jacobs, "Safety and Translation of Calculus Queries with Scalar Functions," Proc. ACM Symp. Principles of Database Systems, pp. 253-264,Washington, D.C., May 1993.
[12] J. Ferrante and C.W. Rackoff, "The Computational Complexity of Logical Theories," Lecture Notes in Math., no. 718, Spinger-Verlag, 1979.
[13] D.M. Gabbay,I. Hodkinson,, and M. Reynolds,Temporal Logic Math. Foundations and Computational Aspects, vol. 1. Oxford Logic Guides, Oxford Univ. Press, 1994.
[14] C.S. Jensen, M.D. Soo, and R.T. Snodgrass, “Unifying Temporal Data Models via a Conceptual Model,” Information Systems, vol. 19, no. 7, pp. 513–547, 1994.
[15] F. Kabanza, J.-M. Stevenne, and P. Wolper, “Handling Infinite Temporal Data,” Proc. ACM SIGACT-SIGMOD-SIGART Symp. Principles of Database Systems, pp. 392-403, Apr. 1990.
[16] M. Niezette and J. Stevenne, "An Efficient Symbolic Representation of Periodic Time," First Int'l Conf. Information and Knowledge Management,Baltimore, Md., Nov. 1992.
[17] R.T. Snodgrass, I. Ahn, G. Ariav, D.S. Batory, J. Clifford, C.E. Dyreson, R. Elmasri, F. Grandi, C.S. Jensen, W. Kafer, N. Kline, K. Kulkanri, T.Y.C. Leung, N. Lorentzos, J.F. Roddick, A. Segev, M.D. Soo, and S.M. Sripada, "TSQL2 Language Specification," SIGMOD Record, vol. 23, no. 1, pp. 65-86, Mar. 1994.
[18] A. Segev and R. Chandra, "A Data Model for Time-Series Analysis," Lecture Notes in Computer Science, no. 759, Springer Verlag, 1993.
[19] Y. Shoham, "Temporal Logics in AI: Semantical and Ontological Considerations," Artificial Intelligence J., vol. 33, pp. 89-104, Feb. 1987.
[20] R.T. Snodgrass, S. Gomez, and E. Mackenzie, “Aggregates in the Temporal Query Language TQuel,” IEEE Trans. Knowledge and Data Eng., vol. 5, no. 5, pp. 826-842, Oct. 1993.
[21] R.T. Snodgrass, “The Temporal Query Language TQuel,” ACM Trans. Database Systems, vol. 12, no. 2, pp. 247–298, 1987.
[22] The TSQL2 Temporal Query Language. R.T. Snodgrass, ed., Kluwer Academic Publishers, 1995.
[23] A. Segev and A. Shoshani, "Logical Modeling of Temporal Data," Proc. ACM SIGMOD Conf. Management of Data, pp. 454-466, May 1987.
[24] A.U. Tansel, "A Statistical Interface for Historical Relational Databases," Proc. Int'l Conf. Data Eng., pp. 538-546,Los Angeles, Feb. 1987.
[25] J. Ullman, Principles of Database and Knowledge-Base Systems, vol. 1. Computer Science Press, 1988.
[26] X. Wang, C. Bettini, A. Brodsky, and S. Jajodia, "Logical Design for Temporal Databases with Multiple Granularities," ACM Trans. Database Systems, to appear, 1997.
[27] X. Wang, S. Jajodia, and V.S. Subrahmanian, "Temporal Modules: An Approach toward Federated Temporal Databases," Proc. 1993 ACM SIGMOD Int'l Conf. Management of Data,Washington, D.C., 1993.
[28] G. Wiederhold, S. Jajodia, and W. Litwin, "Dealing with Granularity of Time in Temporal Databases," Proc. Nordic Conf. Advanced Information Systems Eng., R. Anderson et al., eds., pp. 124-140. Springer, 1991,

Index Terms:
Temporal databases, time granularity, temporal query languages, implicit data, TSQL2.
Claudio Bettini, X. Sean Wang, Sushil Jajodia, "Temporal Semantic Assumptions and Their Use in Databases," IEEE Transactions on Knowledge and Data Engineering, vol. 10, no. 2, pp. 277-296, March-April 1998, doi:10.1109/69.683757
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