Moving objects databases: issues and solutions

Wolfson, Ouri; Xu, Bo; Chamberlain, Sam; Jiang, Liqin

doi:10.1109/ssdm.1998.688116

Cited by 325 publications

(186 citation statements)

References 20 publications

(15 reference statements)

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“…There is ample research on moving object databases (MOD) [25,56,63,64]. Whereas most database research on MOD focuses on data structures, indexing and efficient querying techniques for moving objects [1,16,23,24], only recently the potential of data mining for movement patterns has been acknowledged [31,32,53].…”

Section: Limiting Databasesmentioning

confidence: 99%

Reporting Leaders and Followers among Trajectories of Moving Point Objects

et al. 2007

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Abstract. Widespread availability of location aware devices (such as GPS receivers) promotes capture of detailed movement trajectories of people, animals, vehicles and other moving objects, opening new options for a better understanding of the processes involved. In this paper we investigate spatio-temporal movement patterns in large tracking data sets. We present a natural definition of the pattern 'one object is leading others', which is based on behavioural patterns discussed in the behavioural ecology literature. Such leadership patterns can be characterised by a minimum time length for which they have to exist and by a minimum number of entities involved in the pattern. Furthermore, we distinguish two models (discrete and continuous) of the time axis for which patterns can start and end. For all variants of these leadership patterns, we describe algorithms for their detection, given the trajectories of a group of moving entities. A theoretical analysis as well as experiments show that these algorithms efficiently report leadership patterns.

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Section: Limiting Databasesmentioning

confidence: 99%

Reporting Leaders and Followers among Trajectories of Moving Point Objects

et al. 2007

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“…In a homogeneous space, distances in one part of the space (i.e., differences in content-measure values as points in a 2D space) could be correlated with distances in another part of the space. This type of analysis is important when defining a similarity function based on content measures or when applications deal with moving objects with imprecise positional information [33,41]. In the case of a similarity function, a homogeneous space could easily define a similarity function in terms of distances in the space.…”

Section: Content Measures Under Continues Transformationsmentioning

confidence: 99%

Defining and Comparing Content Measures of Topological Relations

Godoy

Rodrı́guez

2004

GeoInformatica

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This work defines and compares three content measures that characterize topological relations between rectangular regions in a two-dimensional space. These content measures use simplified views of spatial objects in order to create an efficient mechanism for capturing the topological content of spatial configurations. The content measures are compared based on the correlation between two similarity rankings: (1) a similarity ranking defined in terms of the distance of content-measure values and (2) a similarity ranking defined in terms of the error of the geometric adjustment between pairs of objects. The correlation between similarity rankings is used as indicator of how well these content measures characterize topological relations. Such content measures provide mechanisms for creating efficient methods to describe and access information on the basis of the topological content of spatial configurations.

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“…The trajectory adopts an essentially objectbased, Lagrangian perspective on movement, with its focus on entities and their varying locations. In fact, this perspective underlies the overwhelming majority of research on movement within GI science (see, for example, Gudmundsson et al 2008, Soleymani et al 2014, Laube et al 2005, Wolfson et al 1998, Van der Weghe et al 2006.…”

Section: Introductionmentioning

confidence: 99%

A framework for models of movement in geographic space

Wang

Duckham

Worboys

2015

International Journal of Geographical Information Science

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This paper concerns the theoretical foundations of movement informatics. We discuss general frameworks in which models of spatial movement may be developed. In particular, the paper considers the object-field and LagrangianEulerian dichotomies, and the SNAP/SPAN ontologies of the dynamic world, and classifies the variety of informatic structures according to these frameworks. A major challenge is transitioning between paradigms. Usually data is captured with respect to one paradigm but can usefully be represented in another. We discuss this process in formal terms and then describe experiments that we performed to show feasibility. It emerges that observational granularity plays a crucial role in these transitions.

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Moving objects databases: issues and solutions

Cited by 325 publications

References 20 publications

Reporting Leaders and Followers among Trajectories of Moving Point Objects

Reporting Leaders and Followers among Trajectories of Moving Point Objects

Defining and Comparing Content Measures of Topological Relations

A framework for models of movement in geographic space

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