A. Segev and A. Shoshani, "Logical Modelling of Temporal Data," U. Dayal and I. Traiger (eds.), in Proceedings ACM SIGMOD International Conference on Management of Data, 454--466, San Francisco, CA, 1995.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....temporal semantics and developing generalised logical temporal models. A more recent trend has been to develop ways of adding time support to object oriented databases [15] In this research, we have developed a general purpose collection class based on the Time Sequence (TS) model proposed by [14], using a commercial object oriented database called GemStone and its underlying programming language, Smalltalk DB. The TS model is based on the representation of temporal data as totally ordered sequences of time stamped attribute values: s, t, a) where s is the surrogate for the object ....

Segev, A., and Shoshani, A. (1987). Logical modelling of temporal data. Proceedings of the ACM SIGMOD International Conference on Management of Data, San Francisco, CA., pp.454-466.

....in Progress The goal of this research is to design and implement an object oriented temporal database which can be integrated with an information system application, such as decision support system. 4.1. Design Considerations The core data model for the temporal database is derived from Segev and Shoshani (1987). This data model is based on ordered sequences of data values recorded at points in time. Point based temporal representations are better able to handle data which vary continuously (Galton, 1990) and incur reduced processing overheads to ensure integrity in comparison to interval based ....

Segev, A., and Shoshani, A. (1987). Logical modelling of temporal data. Proceedings of the ACM SIGMOD International Conference on Management of Data, San Francisco, CA.

....obtained by adding special (time related) attributes to a relation. These attributes are subject to a specific semantic interpretation. There are few nonrelational proposals: two that are based on the entity relationship model [KL83, AQ86] one that does not depend on a particular data model [SS87, SS88] and some recent proposals that extend the object oriented data model [SC91, KS92, WD92, DW92, PM92] SC91] s proposal does not consider all the implications of introducing temporal issues into the OO paradigm, like inheritance. WD92] s model, though more comprehensive as far as ....

....supported by default in all models analyzed, except [KL83] In this model the user must define a set of functions to determine values not stored. SA86] Sar90a] and [LJ88] support furthermore discrete value evolution. LJ88] uses an operator to simulate other types of interpolation. tod , like [SS87, SS88] and [KRS90] provides support to the four types of value modification. 2.4 Algebraic Operators and Query Language Most models introduce either an algebra or a query language to manipulate temporal constructs. Only three models ( LDE 84] KL83] and [ABN87] propose neither. Algebras ....

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A. Segev and A. Shoshani. Logical modelling of temporal data. In Proc ACM SIGMOD, pages 454--466, 1987.

....the various optimizations into the framework of a single optimization algorithm. For base sequences, the following kinds of meta information may be available in the underlying physical sequence representation 3 : 3 These are similar to the properties associated with a Time Sequence in [SS87, SK86] Sequence Span Density IBM 200 . 500 0.95 DEC 1 . 350 0.7 HP 1 . 750 1.0 Table 1: Example Sequence Data ffl A start and end position that determine the valid range or span of the sequence. Any position outside of this range is mapped to a Null record. ffl A density which specifies ....

....proposes an optimization framework for temporal data based on such techniques. Our approach to sequences presented in this paper takes a strongly positional view of sequences, as opposed to the models mentioned above. In this aspect, it has been influenced by the model of Time Sequences in [SS87, SK86] Research into sequence data in contexts other than temporal data include [GJS92] Ric92] and [SP90] GJS92] presents techniques for expressing and evaluating pattern match queries over a sequence of events. Ric92] presents a model and operators for manipulating lists in a database. ....

Arie Segev and Arie Shoshani. Logical modelling of temporal data. In Proceedings of ACM SIGMOD '87 International Conference on Management of Data, San Francisco, CA, pages 454--466, 1987.

....research, and some topics of ongoing activity and planned future work on SEQ. 7.1 Related Research In Section 2.1, we surveyed the sequence processing capabilities of existing database systems. We now review some research related to this area. Research work directed at modelling time series data [SS87, CS92] provided initial direction to our efforts. The model of a time series in [SS87] is similar to ours, and an SQL like language was also proposed; implementation issues were discussed in the context of how the model could be mapped to a relational data model [SS88] The dual nature of sequences ....

....Research In Section 2.1, we surveyed the sequence processing capabilities of existing database systems. We now review some research related to this area. Research work directed at modelling time series data [SS87, CS92] provided initial direction to our efforts. The model of a time series in [SS87] is similar to ours, and an SQL like language was also proposed; implementation issues were discussed in the context of how the model could be mapped to a relational data model [SS88] The dual nature of sequences (Positional versus Record Oriented) is also recognized by the temporal query ....

Arie Segev and Arie Shoshani. Logical Modelling of Temporal Data. In Proceedings of ACM SIGMOD '87 International Conference on Management of Data, San Francisco, CA, pages 454--466, 1987.

....paper[15] 12] describes operators based on temporal logic for supporting lists in a data model, while [19] provides a model based on logic programing for stream oriented data and processing. Much of this work is similar to our Positional operators on individual sequences. The Time Sequence model[13] views a database as being composed of collections of time varying objects, with query operators over these collections. We show in [15] that the Positional operators of the SEQ model with minor extensions to the Expand operator can represent all Time Sequence queries. 6] presents an ....

Arie Segev and Arie Shoshani. Logical Modelling of Temporal Data. In Proceedings of ACM SIGMOD '87 International Conference on Management of Data, San Francisco, CA, pages 454--466, 1987.

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A. Segev and A. Shoshani, "Logical Modelling of Temporal Data," U. Dayal and I. Traiger (eds.), in Proceedings ACM SIGMOD International Conference on Management of Data, 454--466, San Francisco, CA, 1995.

No context found.

A. Segev and A. Shoshani, "Logical modelling of temporal data". SIGMOD Rec. vol. 16, pp. 454-466, 1987.

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