Chomicki, J. and D. Toman. 1998. "Temporal logic in information systems." In Logics for Databases and Information Systems, edited by J. Chomicki and G. Saake, 31-70. Boston: Kluwer.  Home/Search   Document Details and Download   Summary   Related Articles   Check

....Recently, approaches to temporal reasoning on the Semantic Web have been developed from a functionality centered perspective, e.g. ontology reasoning such as with DAML Time . Temporal knowledge representation and temporal reasoning have been investigated since long, e.g. in (temporal) databases [15, 14, 8, 9] and in Artificial Intelligence [18, 6, 17, 19, 16, 5, 20] Arguably, http: www.cs.rochester.edu ferguson daml temporal reasoning on the Web requires forms of reasoning inherently di#erent from traditional reasoning forms used in databases and Artificial Intelligence because the Web is ....

Jan Chomicki and David Toman. Temporal Logic in Information Systems. In Jan Chomicki, Gunter Saake (Eds.): Logics for Databases and Information Systems, Dagstuhl Seminar: Role of Logics in Information Systems, 1995.

....relationships. If R # gen then R is a binary relationship such that rel(R) #source : E s , target : E t #. The model theoretic semantics associated to the ER VT modelling language adopts the snapshot representation of abstract temporal databases and temporal conceptual models (see e.g. [16]) Following this paradigm, given a For isa relations we use the notation E1 isaE2 instead of #E1 , E2 # # isa. Similarly for disj,cover,dev,dex. flow of time T = #T p , # where T p is a set of time points (or chronons) isomorphic to #Z, #, and a binary precedence relation on T p a ....

....a bitemporal timestamp value recording both the valid and the transaction time of the tuple. The snapshot model is in correspondence with the timestamp model. Indeed, both snapshot databases and the projection over valid time of timestamp databases represent the same class of temporal databases [16]. The following model theoretic semantics for ER VT is in accordance with a snapshot representation of valid time temporal databases. Examples will follow immediately after the definition. Definition 2 (ER VT Semantics) Let # be an ER VT schema, and BD = # D i #D BD i be a set of basic domains ....

J. Chomicki and D. Toman. Temporal logic in information systems. In Chomicki and Saake [15], chapter 1.

....decidable in 2EXPTIME. 1 Introduction Temporal information systems are information systems that store historical information, i.e. past, present, and potential future data [33] Many formalisations have been proposed for temporal information systems which are based on first order temporal logic [17]. Although these formalisations can be very useful for characterising semantical problems arising in temporalised ontologies and in temporal databases, like conceptual modelling or querying, usually they are computationally unfeasible for performing deduction tasks (for example, logical ....

....in the first order temporal logic of the flow of time hZ; i or hN; i is not even recursively enumerable) Note that we are interested in deduction rather than model checking. An obvious solution to this problem would be to look for well behaved fragments of first order temporal logic (see e.g. [17] and references therein) however this way has not been successful the only promising approach we know of is the recent paper [28] Another idea is to deviate from the first order paradigm and start from computationally more friendly languages such as description logics which have been used in ....

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J. Chomicki and D. Toman. Temporal logic in information systems. In Chomicki and Saake [16], chapter 1.

....and logical implication. 1 Introduction Temporal information systems are information systems that store historical information, i.e. past, present, and potential future data. Many formalisations have been proposed for temporal information systems which are based on first order temporal logic [14]. Although these formalisations can be very useful for characterising semantical problems arising in temporalised ontologies and in temporal databases, like conceptual modelling or querying, usually they are computationally unfeasible for performing deduction tasks (for example, logical ....

....in the first order temporal logic of the flow of time # or #N, # is not even recursively enumerable) Note that we are interested in deduction rather than model checking. An obvious solution to this problem would be to look for well behaved fragments of first order temporal logic (see e.g. [14] and references therein) however this way has not been successful the only promising approach we know of is the recent paper [19] Another idea is to deviate from the first order paradigm and start from computationally more friendly languages such as description logics which have been used in ....

[Article contains additional citation context not shown here]

J. Chomicki and D. Toman. Temporal logic in information systems. In Chomicki and Saake [13], chapter 1.

....are summarised for satisfiability and logical implication in DLR US and DLR US , as well as for the query containment problem. 2 The Temporal Description Logic In this paper, we adopt the snapshot representation of abstract temporal databases (and temporal conceptual models) see e.g. [10]. The flow of time T = #T p , #, where T p is a set of time points (or chronons) and a binary precedence relation on T p , is assumed to be isomorphic to #Z, #. Thus, a temporal database can be regarded as a map from time points in T to standard (relational) databases with the ....

....And # = # iff # # ( # #) # # is not satisfiable. Thus, all reasoning tasks connected with the notions introduced above reduce to satisfiability of formulas. The logic DLR US can be regarded as a rather expressive fragment of the firstorder temporal logic L since, until ; cf. [10, 14] and Section 5 below. 1 For instance, we may have #d 1 , d 2 # # (# R) I(t) because #d 1 , d 2 # # R I(t 2) but #d 1 , d 2 # # (# 2 ) I(t 1) 5 3 Temporal queries One more important reasoning task is known as the problem of query containment (see, e.g. 10, 8, 1] for a ....

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J. Chomicki and D. Toman. Temporal logic in information systems. In Chomicki and Saake [9], chapter 1.

.... ( Old(x) SOld(x) at every moment, someone starts to get old ) 1 8x2F (Sub(x) 2F :Sub(x) this is a constraint for temporal databases from [2] an order can be submitted only once ) 3P 9y Works(x; y) 9y Works(x; y) 3F 9y Works(x; y) this is a query to a temporal database from [3]: list all persons who have been unemployed between jobs ) The following formula (one more query from [3] is not monodic: 2P 2F ( 9y (Works(x; y) Works(x; y) Works(x; y) nd all job hoppers people who never spent more than two years in one place ) It turns out that the monodic ....

.... is a constraint for temporal databases from [2] an order can be submitted only once ) 3P 9y Works(x; y) 9y Works(x; y) 3F 9y Works(x; y) this is a query to a temporal database from [3] list all persons who have been unemployed between jobs ) The following formula (one more query from [3]) is not monodic: 2P 2F ( 9y (Works(x; y) Works(x; y) Works(x; y) nd all job hoppers people who never spent more than two years in one place ) It turns out that the monodic fragment of TL(N) though undecidable because it contains full rst order logic, is recursively enumerable, ....

J. Chomicki and D. Toman. Temporal logic in information systems. In J. Chomicki and G. Saake, editors, Logics for Databases and Information Systems, pages 31-70. Kluwer Academic Publishers, 1998.

....DLR US constraints is decidable in 2EXPTIME. 1 Introduction Temporal databases are databases that store historical information, i.e. past, present, and potential future data [27] Many formalisations have been proposed for temporal databases which are based on first order temporal logic [12]. Although these formalisations can be very useful for characterising semantical problems arising in temporal databases, say, conceptual modelling or querying, usually they are computationally unfeasible for performing deduction tasks (for example, logical implication in the first order temporal ....

.... for performing deduction tasks (for example, logical implication in the first order temporal logic of the flow of time #Z, # or #N, # is not even recursively enumerable) An obvious solution to this problem would be to look for well behaved fragments of first order temporal logic (see e.g. [12] and references therein) however this way has not been successful. 1 Another idea is to deviate from the first order paradigm and start from computationally more friendly languages such as description logics which have been used in the area of non temporal databases to characterise in a ....

[Article contains additional citation context not shown here]

J. Chomicki and D. Toman. Temporal logic in information systems. In Chomicki and Saake [11], chapter 1.

....under DLR US constraints is decidable in 2EXPTIME. 1 Introduction Temporal databases are databases that store historical information, i.e. past, present, and potential future data [27] Many formalisations have been proposed for temporal databases which are based on firstorder temporal logic [12]. Although these formalisations can be very useful for characterising semantical problems arising in temporal databases, say, conceptual modelling or querying, usually they are computationally unfeasible for performing deduction tasks (for example, logical implication in the first order temporal ....

.... for performing deduction tasks (for example, logical implication in the first order temporal logic of the flow of time hZ; i or hN; i is not even recursively enumerable) An obvious solution to this problem would be to look for well behaved fragments of first order temporal logic (see e.g. [12] and references therein) however this way has not been successful. 1 Another idea is to deviate from the first order paradigm and start from computationally more friendly languages such as description logics which have been used in the area of non temporal databases to characterise in a uniform ....

[Article contains additional citation context not shown here]

J. Chomicki and D. Toman. Temporal logic in information systems. In Chomicki and Saake [11], chapter 1.

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Chomicki, J. and D. Toman. 1998. "Temporal logic in information systems." In Logics for Databases and Information Systems, edited by J. Chomicki and G. Saake, 31-70. Boston: Kluwer.

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Chomicki, J. and D. Toman. 1998. "Temporal logic in information systems." In Logics for Databases and Information Systems, edited by J. Chomicki and G. Saake, 31-70. Boston: Kluwer.

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Jan Chomicki and David Toman. Temporal Logic in Information Systems. In Jan Chomicki and Gunter Saake, editors, Logics for Databases and Information Systems, pages 31-70. Kluwer, 1998.

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J. Chomicki and D. Toman. Temporal Logic in Information Systems. In J. Chomicki and G. Saake, editors, Logics for Databases and Information Systems, pages 31--70. Kluwer, 1998.

....infinite histories. The chapter concludes with open problems and directions for future research. While the chapter attempts to be self contained and provides most of the necessary definitions, it still assumes a certain level of familiarity with temporal query languages (for a survey see [13]) with basic results on temporal logic [16] and with the relational model [2] 2 Framework for Data Expiration In this section we introduce a basic framework in which data expiration can be studied. The framework is centered around two main notions, the notion of a history of evolution of an ....

....operators, or 2. by adding explicit references to time instants. The first choice leads to various first order temporal logics while the second approach yields a two sorted first order logic (temporal relational calculus) Both these options have been extensively investigated; for a survey see [13]. Finite Histories vs. Infinite Extensions of Histories. When considering the semantics of a query language over histories, we are faced with an additional choice: 1. We can assume that the current history contains complete information about the system and define semantics of queries with ....

[Article contains additional citation context not shown here]

Jan Chomicki and David Toman. Temporal Logic in Information Systems. In Jan Chomicki and Gunter Saake, editors, Logics for Databases and Information Systems, pages 31--70. Kluwer, 1998.

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J. Chomicki and D. Toman. Temporal Logic in Information Systems. In Chomicki and Saake [6], pages 31--70.

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J. Chomicki and D. Toman. Temporal logic in information systems. In J. Chomicki and G. Saake, editors, Logics for Databases and Information Systems. Kluwer, 1998.

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Jan Chomicki and David Toman. Temporal Logic in Information Systems. In Jan Chomicki, Gunter Saake (Eds.): Logics for Databases and Information Systems, Dagstuhl Seminar: Role of Logics in Information Systems, 1995.

No context found.

J. Chomicki and D. Toman. Temporal logic in information systems. In J. Chomicki and G. Saake, editors, Logics for Databases and Information Systems. Kluwer, 1998.

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J. Chomicki and D. Toman, Chapter 3, "Temporal Logic in Information Systems", Logics for Databases and Information Systems, J. Chomicki and G. Saake (eds.), pages 31--70, March 1998.

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J. Chomicki and D. Toman. Temporal Logic in Information Systems. In Logics for Databases and Information Systems, pages 31--70. Kluwer, 1998.

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D. Toman J. Chomicki. Temporal logic in information systems. In Logics for Databases and Information Systems, pages 31--70. Kluwer, 1998.

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D. Toman J. Chomicki. Temporal logic in information systems. In Logics for Databases and Information Systems, pages 31--70. Kluwer, 1998.

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J. Chomicki and D. Toman. Temporal logic in information systems. In Chomicki and Saake [9], chapter 1.

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J. Chomicki and D. Toman. Temporal logic in information systems. In Logics for Databases and Information Systems, J. Chomicki and G. Saake, eds, pp. 31--70. Kluwer Academic Publishers, 1998.

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J. Chomicki and D. Toman. Temporal logic in information systems. In Chomicki and Saake [13], chapter 1.

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J. Chomicki and D. Toman. Temporal logic in information systems. In Chomicki and Saake [9], chapter 1.

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