Research perspectives for time series management systems

Dreyer, Werner; Dittrich, Angelika Kotz; Schmidt, Duri

doi:10.1145/181550.181553

Cited by 34 publications

(21 citation statements)

References 2 publications

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“…We have outlined a temporal algebra that supports clocked relations, that is, relations based on different scales of time such as multiple time series data [15]. Temporal operators are used to navigate through multiple time-lines, and change (restrict) the clocks of resulting relations.…”

Section: Resultsmentioning

confidence: 99%

Querying Historical Data Over Multiple Time-Lines

Orgun

2008

Math.comput.sci.

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In a temporal database, time-varying relations may be defined over multiple time-lines with varying rates of sampling and/or progress, for instance, multiple time series. There is a need to represent such data in a temporal model and provide query languages. In this paper, we propose a clocked temporal relational algebra, called , which supports temporal relations based on multiple time-lines. In the underlying model, temporal relations (historical data) are defined over clocks which are subsequences of an assumed global time-line. The algebra is uniform, it is a consistent extension of the relational algebra, and it includes a number of temporal operators to combine data based on different time-lines, as well as extensions of the operators of the relational algebra. The semantics of an operation of depends on the clocks of the relations involved in the operation as well as the relations. We outline a formal interpretation of expressions of , which also represent clocked relations, and sketch a naïve expression evaluation method.

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Section: Resultsmentioning

confidence: 99%

Querying Historical Data Over Multiple Time-Lines

Orgun

2008

Math.comput.sci.

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“…Their time series structures include the notion of regularity and temporal representation and their operations are SQL-like. Dreyer et al [4] suggest the requirements of a particular purpose TSMS and base the model on five basic structural elements: events, time series, groups, metadata and time series basis. They implement a TSMS named Calanda which includes calendar operations, it allows grouping of time series, and it operates with simple queries.…”

Section: Database Approachesmentioning

confidence: 99%

“…These systems are generically known as Time Series Database Management Systems (TSMS) [4,5]. However, as shown below, most of them exhibit some drawbacks when trying to solve the challenging issues of time series in the temporal data domain.…”

Section: Introductionmentioning

confidence: 99%

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Formalism for a multiresolution time series database model

Serra

Vila-Marta

Escobet

2016

Information Systems

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We formalise a specialised database management system model for time series using a multiresolution approach. These special purpose database systems store time series lossy compressed in a space-bounded storage. Time series can be stored at multiple resolutions, using distinct attribute aggregations and keeping its temporal attribute managed in a consistent way.\ud \ud The model exhibits a generic approach that facilitates its customisation to suit better the actual application requirements in a given context. The elements, the meaning of which depends on a real application, are of generic nature.\ud \ud Furthermore, we consider some specific time series properties that are a challenge in the multiresolution approach. We also describe a reference implementation of the model and introduce a use case based on real data.Peer ReviewedPostprint (author's final draft

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“…The reason for this importance is the increasing application of empirical methods with more and more data. However, the data intensity causes several problems (see [4] for a detailed discussion):…”

Section: Introductionmentioning

confidence: 99%