The representation of a temporal data model in the relational environment

Segev, Arie; Shoshani, Arie

doi:10.1007/bfb0027504

Cited by 27 publications

(14 citation statements)

References 18 publications

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“…Similar to our approach, in (Yeh et al, 1993(Yeh et al, , 1995 based on the work in (Segev et al, 1993) so-called behavioral time sequences are introduced. Each element of such a sequence contains a geometric value, a date, and a behavioral function, the latter describing the evolution between two consecutive elements of the sequence.…”

Section: Related Workmentioning

confidence: 99%

Query-by-Trace: Visual Predicate Specification in Spatio-Temporal Databases

Erwig

Schneider

2000

Advances in Visual Information Management

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In this paper we propose a visual interface for the specification of predicates to be used in queries on spatio-temporal databases. The approach is based on a visual specification method for temporally changing spatial situations. This extends existing concepts for visual spatial query languages, which are only capable of querying static spatial situations. We outline a preliminary user interface that supports the specification on an intuitive and easily manageable level, and we describe the design of the underlying visual language. The visual notation can be used directly as a visual query interface to spatio-temporal databases, or it can provide predicate specifications that can be integrated into textual query languages leading to heterogeneous languages.

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Section: Related Workmentioning

confidence: 99%

Query-by-Trace: Visual Predicate Specification in Spatio-Temporal Databases

Erwig

Schneider

2000

Advances in Visual Information Management

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“…Ariav [7] also introduces a temporallyoriented data model (as a restricted superset of the relational model) and provides a SQL-like query language for storing and retrieving temporal data. The works of Mahmood et al [25] and Segev and Shoshani [33] go into a similar direction. The later also investigate the semantics of temporal data and corresponding operators independently from a specific data model in [32].…”

Section: Related Workmentioning

confidence: 83%

A Native Versioning Concept to Support Historized Models at Runtime

Hartmann

Fouquet

Nain

et al. 2014

Lecture Notes in Computer Science

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Abstract. Models@run.time provides semantically rich reflection layers enabling intelligent systems to reason about themselves and their surrounding context. Most reasoning processes require not only to explore the current state, but also the past history to take sustainable decisions e.g. to avoid oscillating between states. Models@run.time and model-driven engineering in general lack native mechanisms to efficiently support the notion of history, and current approaches usually generate redundant data when versioning models, which reasoners need to navigate. Because of this limitation, models fail in providing suitable and sustainable abstractions to deal with domains relying on history-aware reasoning. This paper tackles this issue by considering history as a native concept for modeling foundations. Integrated, in conjunction with lazy load/storage techniques, into the Kevoree Modeling Framework, we demonstrate onto a smart grid case study, that this mechanisms enable a sustainable reasoning about massive historized models.

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“…For example, in the MANAGER. relation of Fig.l There are various ways to represent temporal data in the relational model; detailed discussion can be found in [17]. In this paper we assume first normal form relations (INF).…”

Section: Relational Representation Of Temporal Datamentioning

confidence: 99%

“…The main focus of research in temporal databases has been on the modeling and representation of temporal data [4][5][6], [13], [16][17][18][19][20], [22]. Until recently, concerns about the performance of temporal databases have, to a large extent, been ignored.…”

Section: Introductionmentioning

confidence: 99%

“…Until recently, concerns about the performance of temporal databases have, to a large extent, been ignored. There are two major issues that separate the physical design of temporal databases from conventional ones: the size of data, which may be several orders of magnitude larger; and the extended semantics of temporal queries, e.g., [5], [17], [8], [15], which increase the complexity of query pr0-cessing. Previous studies in physical temporal database design tended to focus on narrowly defined objectives.…”

Section: Introductionmentioning

confidence: 99%

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