C. Bettini, X. Wang, E. Bertino, and S. Jajodia. Semantic Assumptions and Query Evaluation in Temporal Databases. In Proc. ACM SIGMOD Int'l. Conf. on Management of Data, pages 257--268, 1995.  Home/Search   Document Not in Database   Summary   Related Articles   Check

.... in tnls tutorial Nonlinear temporal domains: branching time has potential database applications in versioning and workflows [Attie et al. 1993] proposals too preliminary Multiple time granularities: important practical issue many possible approaches [Ladkin, 1986, Wang et al. 1993, Bettini et al. 1995] x MUltiple temporal almenslons To model multiple kinds of time: valid time vs. transaction time To represent intervals using pairs of points. To represent multiple temporal attributes in query results. Data models Query languages Expressive power v. Rsl:rac lemporal ual:a13ases ....

Bettini, C., Wang, X., Bertino, E., and Jajodia, S. (1995). Semantic Assumptions and Query Evaluation in Temporal Databases. In ACM SIGMOD International Conference on Management of Data, pages 257-268, San Jose, Cal- ifornia.

....the time sequences are very long. These are the motivations for this paper. In [8] an extended SELECT operator (o ) was men tioned that denotes selecting implicit states from S l, S 2 . S n based on the step wise constant assumption. But no implementation was discussed. A recent paper [5] points out that by the step wise constant assumption, a database DB can be seen as a larger data base DB that contains both explicit and implicit information. It suggests that a user query Q can be transformed into a system query Q . Q contains the step wise constant assumption so that ....

....independent of any data model and physical implementation, a time sequence is denoted as a sequence of states TS S l, S2, Sn where S i = t i, vi) i = 1, 2. n) By associating a userdefined interpolation function ifn with it, TS will be transformed into TS (following the same notation as [5]) TS is a continuous time sequence defined over the time interval It l, tn] by applyin g ifn on the discrete TS. A SELECT operator o on TS returns sub sequences (time intervals) where the values or time stamps inside those intervals satisfy some conditions, i.e. o(TS) t , t ) In the ....

C. Bettini, X. S. Wang, E. Bertino and S. Jajoda: "Semantic Assumptions and Query Evaluation in Temporal Databases", Proceedings of SIGMOD Conference, May 1995.

....One example is the mediation of temporal data of differing granularity. This is of particular importance in the context of multidimensional databases and data warehousing applications, where historical data is integrated and analyzed for patterns and interesting properties. A temporal mediator [40 42] consists of three components: 1) a repository of windowing functions and conversion functions, 2) a time unit thesaurus, and 3) a query interpreter. There are two types of windowing functions: the first associates time points to sets of object instances, and the other associates object instances ....

C. Bettini, X. S. Wang, E. Bertino, and S. Jajodia, Semantic Assumptions and Query Evaluation in Temporal Databases, presented at ACM SIGMOD International Conference on Management of Data, San Jose, CA, 1995.

....and discrete domains of time. This allows a temporal model to provide support not only for applications which usually need a discrete temporal domain, but also for applications that need dense time as an abstraction. This is in contrast to recent proposals that handle multiple granularities [4, 13, 5, 18, 2, 17, 15]. These proposals assume a single underlying temporal domain which is usually discrete. The contributions of this paper can be summarized as follows: 1) We present a simple, general framework for supporting temporal primitives which allows seamless integration of dense and discrete domains of ....

C. Bettini, X. Wang, E. Bertino, and S. Jajodia. Semantic Assumptions and Query Evaluation in Temporal Databases. In Proc. ACM SIGMOD Int'l. Conf. on Management of Data, pages 257--268, 1995.

....the time sequences are very long. These are the motivations for this paper. In [8] an extended SELECT operator (s ) was mentioned that denotes selecting implicit states from S 1 , S 2 , S n based on the step wise constant assumption. But no implementation was discussed. A recent paper [5] points out that by the step wise constant assumption, a database DB can be seen as a larger database DB that contains both explicit and implicit information. It suggests that a user query Q can be transformed into a system query Q . Q contains the step wise constant assumption so that ....

....of any data model and physical implementation, a time sequence is denoted as a sequence of states TS = S 1 , S 2 , S n where S i = t i , v i ) i = 1, 2. n) By associating a userdefined interpolation function ifn with it, TS will be transformed into TS (following the same notation as [5]) TS is a continuous time sequence defined over the time interval [t 1 , t n ] by applying ifn on the discrete TS. A SELECT operator s on TS returns sub sequences (time intervals) where the values or time stamps inside those intervals satisfy some conditions, i.e. s(TS) t , t ) In the ....

C. Bettini, X. S. Wang, E. Bertino and S. Jajoda: "Semantic Assumptions and Query Evaluation in Temporal Databases", Proceedings of SIGMOD Conference, May 1995.

....because it introduces a new notion of bitemporal element . Moreover, translations between this model and other temporal data models are expressed using an ad hoc procedural language. Recent work on the interoperability of temporal databases, e.g. Wang, Jajodia and Subrahmanian [WJS93, BWBJ95] addresses similar concerns as the present paper. However, the paper [WJS93] does not address spatial or spatiotemporal database issues and makes very strong assumptions about the concrete temporal databases that are to be interoperated. In particular, such databases have to provide a unified ....

....about the concrete temporal databases that are to be interoperated. In particular, such databases have to provide a unified interface. This is not necessary in our approach. Moreover, the data expressiveness of the cited model is limited to sets of finite unrestricted databases. A follow up work [BWBJ95] demonstrates a systematic approach of deriving implicit temporal information from the explicit information stored in a temporal database. Such derivations could very well be incorporated into our framework. For surveys of temporal query languages, see [Cho94, CT98] Spatiotemporal data models ....

C. Bettini, X.S. Wang, E. Bertino, and S. Jajodia. Semantic Assumptions and Query Evaluation in Temporal Databases. In ACM SIGMOD International Conference on Management of Data, pages 257--268, San Jose, California, May 1995.

....because it introduces a new notion of bitemporal element . Moreover, translations between this model and other temporal data models are expressed using an ad hoc procedural language. Current work on the interoperability of temporal databases, e.g. Wang, Jajodia and Subrahmanian [WJS93, BWBJ95] addresses similar concerns as the present paper. However, the paper [WJS93] does not address spatial or spatiotemporal database issues and makes very strong assumptions about the concrete temporal databases that are to be interoperated. In particular, such databases have to provide a unified ....

....about the concrete temporal databases that are to be interoperated. In particular, such databases have to provide a unified interface. This is not necessary in our approach. Moreover, the data expressiveness of the cited model is limited to sets of finite unrestricted databases. A follow up work [BWBJ95] demonstrates a systematic approach of deriving implicit temporal information from the explicit information stored in a temporal database. Such derivations could very well be incorporated into our framework. There is a quickly growing list of papers on various aspects of constraint databases. The ....

C. Bettini, X.S. Wang, E. Bertino, and S. Jajodia. Semantic Assumptions and Query Evaluation in Temporal Databases. In ACM SIGMOD International Conference on Management of Data, pages 257--268, San Jose, California, May 1995.

....and discrete domains of time. This allows a temporal model to provide support not only for applications which usually need a discrete temporal domain, but also for applications that need dense time as an abstraction. This is in contrast to recent proposals that handle multiple granularities [4, 13, 5, 18, 2, 17, 15]. These proposals assume a single underlying temporal domain which is usually discrete. The contributions of this paper can be summarized as follows: 1) We present a simple, general framework for supporting temporal primitives which allows seamless integration of dense and discrete domains of ....

C. Bettini, X. Wang, E. Bertino, and S. Jajodia. Semantic Assumptions and Query Evaluation in Temporal Databases. In Proc. ACM SIGMOD Int'l. Conf. on Management of Data, pages 257--268, 1995.

....each case, that the propagation algorithm is correct, although the first method generally yields better solutions. In various parts of the paper, we also briefly mention applications of the temporal type systems and constraint networks. These applications are essentially from our previous papers [WJS95, WBBJ97, BWBJ95, BWJ96]. The rest of the paper is organized as follows. In Section 2, definitions of temporal types and temporal type systems are given, and some properties of types and type systems are discussed. In Section 3, constraint networks with multiple granularities are introduced, and the problem of their ....

....the system are equivalent with respect to shifting of their indices. Restriction (a) is indeed enforced by the condition that the first non empty tick (if any) must start with index 1 (second condition in the definition of T T S 1 ) An example of a more restrictive granularity system is given in [WJS95, BWBJ95] where a discrete absolute time and index sets (both positive integers) are used, and restrictions (1) 2) 3) and (a) apply. In this paper we refer to this temporal type system as T T S 2 . It can be easily seen that each type in T T S 2 corresponds to a partition of the positive integers such ....

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C. Bettini, X. Wang, E. Bertino, and S. Jajodia, Semantic assumptions and query evaluation in temporal databases, in Proc. of ACM SIGMOD, San Jose, CA, 1995, pp. 257--268. 24

....false otherwise. In order words, IntSec ; i; j) is true iff the intersection of the corresponding absolute time intervals of tick i of and tick j of is not empty. For instance, IntSec month;year (i; j) is true iff the month i falls within the year j. 2 This subsection borrows heavily from [BWBJ95] 3 An interval [i; j] i; 1] resp. is viewed as the set of all integers k such that i k j (k i, resp. 5 3.2 Temporal module schemes and temporal modules We assume there is a set of attributes and a set of values called the data domain. Each finite set R of attributes is called a ....

....equality. Note that TCALC formulas are similar to MFO formula, except that MFO has no temporal module predicates M( and no data variables. A TCALC query is of the form fx 1 : x k ; i 1 ; i n : j (x 1 ; x k ; i 1 ; i n )g 4 Here again, we borrow heavily from [BWBJ95] for the definition of TCALC. 13 where x 1 : x k are variable names or constants of the data sort, i 1 , i n are temporal variables or constants of (the same) type , and (x 1 ; x k ; i 1 ; i n ) is a TCALC formula whose only free variables are among x 1 ; x ....

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C. Bettini, X. Wang, E. Bertino, and S. Jajodia. Semantic assumptions and query evaluation in temporal databases. In Proc. ACM SIGMOD Int. Conf. on Management of Data. ACM, 1995. To appear.

....are equivalent with respect to shifting of their indices. This last restriction is enforced by the condition that the first non empty tick (if any) must start with index 1 (condition 2 in the definition of T T S 1 ) An example of a more restrictive granularity system is the one we defined in [WJS95, BWBJ95] where a discrete absolute time and index set (positive integers) are used. Furthermore, no gaps are allowed in a tick (i.e. each tick is an interval on positive integers) and two ticks with consecutive index values must be contiguous (i.e. i) i 1) is an interval or the empty set for all ....

....a database the rainfall amounts for each day, record income for each year, and so on. It is sometimes desirable to obtain the rainfall amount of a month. Here, the information about rainfall is viewed as converted into that in terms of month. The conversion function used is the summation. In [BWBJ95], we proposed a framework for specifying such information conversion and studied related query evaluation problems. 3 Temporal constraints with granularities In the temporal reasoning area a lot of work has been done on formalisms to express networks of constraints and on algorithms to solve ....

[Article contains additional citation context not shown here]

C. Bettini, X. Wang, E. Bertino, and S. Jajodia. Semantic assumptions and query evaluation in temporal databases. In Proc. of ACM SIGMOD-95, pages 257-- 268, San Jose,CA, 1995.

No context found.

C. Bettini, X.S. Wang, E. Bertino, S. Jajodia. Semantic Assumptions and Query Evaluation in Temporal Databases. In , pages 257--268, 1995.

No context found.

C. Bettini, X. Wang, E. Bertino, and S. Jajodia. Semantic Assumptions and Query Evaluation in Temporal Databases. In Proc. ACM SIGMOD Int'l. Conf. on Management of Data, pages 257--268, 1995.

No context found.

C. Bettini, X. S. Wang, E. Bertino, S. Jajodia. Semantic Assumptions and Query Evaluation in Temporal Databases. In Proc. SIGMOD Conf., pp. 257-268, May 1995.

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