How Would You Like to Aggregate Your Temporal Data?

Böhlen, Michael H.; Gamper, Johann; Jensen, Christian S.

doi:10.1109/time.2006.17

Cited by 23 publications

(12 citation statements)

References 31 publications

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“…As an example, two consecutive phone calls with the same values are different from a single phone call over the whole period. This is also the case for some kinds of temporal aggregation [BGJ06]. Finally, the use of time intervals is common in several areas of AI, including knowledge representation and qualitative reasoning, e.g., [AF94].…”

Section: Scientific Fundamentalsmentioning

confidence: 99%

Time in Philosophical Logic

Øhrstrøm¹,

Hasle²

2016

Encyclopedia of Database Systems

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Section: Scientific Fundamentalsmentioning

confidence: 99%

Time in Philosophical Logic

Øhrstrøm¹,

Hasle²

2016

Encyclopedia of Database Systems

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“…Several papers have addressed aggregation for temporal and spatio-temporal data including instantaneous temporal aggregation [21], cumulative temporal aggregation [22], [23], [24], histogram-based aggregation [25], and multi-dimensional temporal aggregation [26]. These techniques differ in how a time line is partitioned into time intervals and how an aggregation group is associated with each time instant.…”

Section: Related Workmentioning

confidence: 99%

Aggregating and Disaggregating Flexibility Objects

Šikšnys

Valsomatzis

Hose

et al. 2015

IEEE Trans. Knowl. Data Eng.

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In many scientific and commercial domains we encounter flexibility objects, i.e., objects with explicit flexibilities in a time and an amount dimension (e.g., energy or product amount). Applications of flexibility objects require novel and efficient techniques capable of handling large amounts of such objects while preserving flexibility. Hence, this paper formally defines the concept of flexibility objects (flex-objects) and provides a novel and efficient solution for aggregating and disaggregating flex-objects. Out of the broad range of possible applications, this paper will focus on smart grid energy data management and discuss strategies for aggregation and disaggregation of flex-objects while retaining flexibility. This paper further extends these approaches beyond flex-objects originating from energy consumption by additionally considering flex-objects originating from energy production and aiming at energy balancing during aggregation. In more detail, this paper considers the complete life cycle of flex-objects: aggregation, disaggregation, associated requirements, efficient incremental computation, and balance aggregation techniques. Extensive experiments based on real-world data from the energy domain show that the proposed solutions provide good performance while satisfying the strict requirements.

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“…For simplicity and without loss of generality, time is discretized into equalsized units, e.g., 15 minute intervals, and we have only one amount dimension (i.e., D = 1). Figure 1 depicts the example of a flex-object having a profile with four slices: s (1) , s (2) , s (3) , and s (4) . Every slice is represented by a bar in the figure.…”

Section: Problem Formulationmentioning

confidence: 99%

“…The left and the right sides of a bar represent t e and t s of a slice, respectively. s (2) s (3) s (4) Amount/slice duration We distinguish two types of flexibility associated with f . The time flexibility, tf (f ), is the difference between the latest and earliest start time.…”

Section: Problem Formulationmentioning

confidence: 99%

Aggregating and Disaggregating Flexibility Objects

Šikšnys

Khalefa

Pedersen

2012

Lecture Notes in Computer Science

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Flexibility objects, objects with flexibilities in time and amount dimensions (e.g., energy or product amount), occur in many scientific and commercial domains. Managing such objects with existing DBMSs is infeasible due to the complexity, data volume, and complex functionality needed, so a new kind of flexibility database is needed. This paper is the first to consider flexibility databases. It formally defines the concept of flexibility objects (flex-objects), and provide a novel and efficient solution for aggregating and disaggregating flex-objects. This is important for a range of applications, including smart grid energy management. The paper considers the grouping of flex-objects, alternatives for computing aggregates, the disaggregation process, their associated requirements, as well as efficient incremental computation. Extensive experiments based on data from a real-world energy domain project show that the proposed solution provides good performance while still satisfying the strict requirements.

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How Would You Like to Aggregate Your Temporal Data?

Abstract: Published in: Proceedings of the 13th International Symposium on Temporal

Cited by 23 publications

References 31 publications

Time in Philosophical Logic

Time in Philosophical Logic

Aggregating and Disaggregating Flexibility Objects

Aggregating and Disaggregating Flexibility Objects

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