C.S. Jensen and R. Snodgrass: "Semantics of Time-Varying Information", Information Systems, Vol.21, No.4, pp.311-352, 1996.  Home/Search   Document Details and Download   Summary   Related Articles   Check

....approach is also more generally useful for other applications that involve cyclic phenomena. 1.1 Linear vs. Cyclic Phenomena Discussions within the database community on modeling time varying phenomena have resulted in many models reflecting different views of the semantics associated with time [10]. Numerous approaches exist for modeling time, although time is most often discussed with respect to two key structural models: linear and branching models of time. The most general model of time in a temporal logic represents time as an arbitrary, partially ordered set [11, 12] The addition of ....

Jensen, C. and R. Snodgrass. Semantics of time-varying information. Information Systems, 1996. 21(4): p. 311-352.

....1. Introduction Database applications often need to capture the timevarying nature of an enterprise they model. The importance of such need has been recognized by several database research groups, and temporal database models and query languages have been developed and reported in the literature [8, 13]. In fact, there are several temporal query languages supporting temporal aggregation [12] However, temporal data and queries provide many unique characteristics and challenges for query processing and optimization. Among the challenges is computing temporal aggregates, which is complicated by ....

Christian S. Jensen and Richard T. Snodgrass. Semantics of time-varying information. 21(4):311--352, 1996.

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# C.S. Jensen and R.T. Snodgrass, "Semantics of Time-Varying Information, " Information Systems, vol. 21, no. 4, pp. 311--352, 1996.

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C. S. Jensen and R. Snodgrass. Semantics of Time-Varying Information. Information Systems, 21(4):311--352 (1996).

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C. S. Jensen and R. Snodgrass. Semantics of TimeVarying Information. Information Systems, 21(4):311--352 (1996).

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C.S. Jensen and R.T. Snodgrass, "Semantics of Time-varying Information," Information Systems 21(4), 311--352, 1996.

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C. S. Jensen and R. T. Snodgrass, "Semantics of Time-Varying Information," Information Systems, Vol. 21, No. 4, pp. 311-352, 1996.

....timestamp includes Until Changed (UC) which is a special transaction time marker. If the transaction time includes UC, the associated fact is current in the database. An uninterpreted time value is referred to as user defined time [34] Time varying data may be modeled as an event or a state [33]. An event occurs at a point of time, i.e. an event has no duration. In other words, an event is instantaneous and its occurrence results in a fact becoming true. A state has duration, e.g. a storm occurred from 5:07 PM to 5:46 PM. An event and a state are associated with a temporal ....

....or the associated temporal constraints. Figure 3 also shows the semantics of a temporal entity class in ST USM via a mapping using the concepts of a conventional conceptual model; we refer to it as a translated USM schema. This mapping from ST USM to (translated) USM are snapshot equivalent [33], i.e. the two schemas (ST USM and translated USM) represent the same information content over snapshots taken at all times. In order to express the semantics of a temporal entity class, we need to specify a TEMPORAL GRANULARITY in which the evolution of a temporal object is embedded. The ....

C. S. Jensen and R. T. Snodgrass, Semantics of Time-Varying Information,Information Systems, Vol. 21, No. 4, pp. 311-352, 1996.

....made hundreds of times, so it is important to know both when the data is considered to be valid in the real world, and when it is stored and changed in the database. These temporal aspects of the data, known as valid time and transaction time, must both be supported to provide bitemporal support [12]. This support is for instance needed in order to couple different facts, e.g. smoking and weight, thereby computing snapshots of measurement values at specific intervals or points in time 3 . These snapshots are used to observe temporal trends in the evolution of one type of data values ....

C. S. Jensen and R. T. Snodgrass. Semantics of Time-Varying Information. Information Systems, 21(4):311--352, March 1996.

....are considered in isolation, followed by a short discussion of current time variables in bitemporal databases. 2. 1 Storing Valid time Variables in Databases The valid time of a fact denotes the time(s) when the fact is true in the modeled reality [Jensen et al. 1994a, Snodgrass and Ahn 1985, Jensen and Snodgrass 1996] In the valid time dimension, a timestamp involving now is commonly used to indicate that a fact is currently valid [Ariav et al. 1984, Bassiouni and Llewellyn 1992, Elmasri et al. 1990, Gadia 1988, Navathe and Ahmed 1989, Sarda 90, Tansel 1990, Yau and Chat 1991] It is possible to explicitly ....

C. S. Jensen and R. T. Snodgrass "Semantics of Time-Varying Information, " Information Systems , to appear.

....of application. Two temporal aspects of data are generally considered fundamental. The valid time of a fact is the time(s) past, present, or future, when the fact is true in the modeled reality, while the transaction time of a fact is the time(s) when the fact was or is current in the database [9, 16]. Data with both valid and transaction time associated is termed bitemporal. Full spatiotemporal support implies considering these two temporal aspects as well as two or three dimensions of space. The previously proposed spatiotemporal indices [19, 13] assume only one time dimension, adopting one ....

....but retaining it in the database. A modification is modeled as a deletion followed by an insertion (e.g. an update led to Tuples 4 and 5) The temporal aspects of a tuple can be represented graphically by a two dimensional ( bitemporal ) region in the space spanned by transaction and valid time [9]. Figure 1 illustrates the bitemporal regions of the tuples from Table 1. A now relative transaction time interval yields a rectangle that grows in the transaction time direction as time passes (Tuple 1) Having both transaction and valid time intervals being now relative yields a stair shaped ....

C. S. Jensen and R. Snodgrass. Semantics of Time-Varying Information. Information Systems, 21(4):311--352 (1996).

....in valid time and transactiontime databases are considered in isolation, followed by a short discussion of currenttime variables in bitemporal databases. 2. 1 Storing Valid time Variables in Databases The valid time of a fact denotes the time(s) when the fact is true in the modeled reality [33, 47, 32]. In the valid time dimension, a timestamp involving now is commonly used to indicate that a fact is currently valid [2, 3, 22, 25, 40, 43, 49, 53] It is possible to explicitly record when facts are valid in both conventional SQL databases and in truly temporal, e.g. TSQL2 [46] databases. With ....

C. S. Jensen and R. T. Snodgrass "Semantics of Time-Varying Information," Information Systems, to appear.

....that is competitive with the best existing index; and unlike this existing index, the new technique does not require extension of the kernel of the DBMS. 1187 1188 IMPLEMENTATION TECHNIQUES 1 Introduction Two temporal aspects of data are fundamental valid time and transaction time [SA85] [JS96]. The valid time of a database tuple is the time when the tuple is true in the modeled reality, the mini world. A tuple s transaction time is the time during which the tuple is current in the database. These temporal aspects of data are essential in a wide range of existing, real world ....

....more detail the nature of bitemporal data, then characterizes the different kinds of two dimensional bitemporal data regions. As mentioned in the previous section, valid time captures when a tuple is true in the modeled reality, and transaction time captures when a tuple is current in the database [SA85, JS96]. These two temporal aspects are orthogonal in that each could be recorded independently, and each has specific properties associated with it. The valid time of a tuple can be in the past or in the future (allowing to store information about the past and the future) and can be changed freely. In ....

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C. S. Jensen and R. Snodgrass. Semantics of Time-Varying Information. Information Systems, 21(4):311--352 (1996).

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C. S. Jensen and R. T. Snodgrass. Semantics of Time-varying Information. Information Systems, 21(4):311--352, 1996.

....are reduced. Performance studies indicate that the best extended index is typically 3 5 times faster than the existing R tree based indices. 1161 1162 IMPLEMENTATION TECHNIQUES 1 Introduction Data stored in a database has two fundamental temporal aspects valid time and transaction time [14, 8]. The valid time of a database fact is the time when the fact is true in the modeled reality, while the fact s transaction time is the time during which it is current in the database. Valid and transaction time are orthogonal in that each could be independently recorded, and each has specific ....

....a tuple can be represented graphically by a twodimensional ( bitemporal ) region in the space spanned by valid and transaction 1 We use closed intervals and let [TTbegin, TTend] denote the interval that includes TTbegin and TTend. R TREE BASED INDEXING OF NOW RELATIVE BITEMPORAL DATA 1165 time [8]. Cases 1 5 in Figure 1 illustrate the bitemporal regions of Tuples (1 4) and (6) respectively. A now relative transaction time interval yields a rectangle that grows in the transaction time direction as time passes (Tuple (1) Case 1) Having both transaction and valid time intervals being ....

C. S. Jensen and R. Snodgrass. Semantics of Time-Varying Information. Information Systems, 21(4):311--352 (1996).

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C. S. Jensen and R. T. Snodgrass. Semantics of Time-Varying Information. Information Systems, 21(4):311--352 (1996).

....is used solely as a design model or is also used as an implementation model, complete with database instances and a query language. Support for Interpolation Temporal interpolation functions derive information about times for which no data is explicitly stored in the database (see, e.g. 20] and [18]) For example, it is possible to record times when new salaries of employees take effect and then define an interpolation function (using so called step wise constant interpolation) that gives the salaries of employees at any time during their employment. In the scientific domain, interpolation ....

C. S. Jensen and R. T. Snodgrass. Semantics of Time-Varying Information. Information Systems, 21(4):311--352, March 1996.

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C. S. Jensen and R. Snodgrass. Semantics of Time-Varying Information. In Information Systems 21(4): 311-352. (1996)

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C. S. Jensen and R. Snodgrass. Semantics of Time-Varying Information. Information Systems, 21(4):311--352 (1996).

....It describes temporal star schemas and provides a case based, empirical comparison of temporal star schemas with regular star schemas, considering database size and query performance, as well as the ease of formulating queries. The temporal star schemas considered here capture valid time [6, 11], the time when the facts stored in the database are true in the modeled reality. The novel notion of temporal star schemas was introduced in a white paper by Leep Technology, Inc. 9] While the performance of various representation schemas for temporal data has been the object of study (e.g. ....

C. S. Jensen and R. Snodgrass. Semantics of Time-Varying Information. Information Systems 21(4): 311-352 (1996).

....the new technique yields a performance that is competitive with the best existing index; and unlike this existing index, the new technique does not require extension of the kernel of the DBMS. 1 Introduction Two temporal aspects of data are fundamental valid time and transaction time [SA85] [JS96]. The valid time of a database tuple is the time when the tuple is true in the modeled reality, the mini world. A tuple s transaction time is the time during which the tuple is current in the database. These temporal aspects of data are essential in a wide range of existing, real world ....

....more detail the nature of bitemporal data, then characterizes the different kinds of two dimensional bitemporal data regions. As mentioned in the previous section, valid time captures when a tuple is true in the modeled reality, and transaction time captures when a tuple is current in the database [SA85, JS96]. These two temporal aspects are orthogonal in that each could be recorded independently, and each has specific properties associated with it. The valid time of a tuple can be in the past or in the future (allowing to store information about the past and the future) and can be changed freely. In ....

[Article contains additional citation context not shown here]

C. S. Jensen and R. Snodgrass. Semantics of Time-Varying Information. Information Systems, 21(4):311--352 (1996).

....problems. It describes temporal star schemas and provides a case based, empirical comparison of temporal star schemas with regular star schemas, considering database size and query performance, as well as the ease of formulating queries. The temporal star schemas considered here capture valid time [6, 11], the time when the facts stored in the database are true in the modeled reality, as an opposite to transaction time, which concerns when the facts are current in the database. The novel notion of temporal star schemas was introduced in a white paper by Leep Technology, Inc. 9] While the ....

C. S. Jensen and R. Snodgrass. Semantics of Time-Varying Information. Information Systems, 21(4):311-352 (1996).

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C.S. Jensen and R. Snodgrass: "Semantics of Time-Varying Information", Information Systems, Vol.21, No.4, pp.311-352, 1996.

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Jensen CS, Snodgrass R (1996) Semantics of time-varying information. Inf Syst 21(4):311--352

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C. S. Jensen and R. T. Snodgrass. Semantics of time-varying information. Information Systems, 21#4#:311#352, 1996.

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