A multigranular spatiotemporal data model

Camossi, Elena; Bertolotto, Michela; Bertino, Elisa; Guerrini, Giovanna

doi:10.1145/956676.956689

Cited by 27 publications

(19 citation statements)

References 12 publications

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“…Few works addressed multiple representations of spatial on moving objects [11] [7]. We rely on our own previous work [3][25] to handle multiple representations of trajectories in the same way we did for other data.…”

Section: Related Workmentioning

confidence: 99%

A conceptual view on trajectories

Spaccapietra

Parent

Damiani

et al. 2008

Data & Knowledge Engineering

512

376

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Analysis of trajectory data is the key to a growing number of applications aiming at global understanding and management of complex phenomena that involve moving objects (e.g. worldwide courier distribution, city traffic management, bird migration monitoring). Current DBMS support for such data is limited to the ability to store and query raw movement (i.e. the spatio-temporal position of an object). This paper explores how conceptual modeling could provide applications with direct support of trajectories (i.e. movement data that is structured into countable semantic units) as a first class concept. A specific concern is to allow enriching trajectories with semantic annotations allowing users to attach semantic data to specific parts of the trajectory. Building on a preliminary requirement analysis and an application example, the paper proposes two modeling approaches, one based on a design pattern, the other based on dedicated data types, and illustrates their differences in terms of implementation in an extended-relational context.

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Section: Related Workmentioning

confidence: 99%

A conceptual view on trajectories

Spaccapietra

Parent

Damiani

et al. 2008

Data & Knowledge Engineering

512

376

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“…A line segment that changes direction with time is represented as two line segments that shrink to points in one or the other end of the time slice. A way to specify multiple granularities for both space and time in models for independent spatiotemporal objects is given in [11].…”

Section: Related Workmentioning

confidence: 99%

Representing topological relationships for spatiotemporal objects

Tøssebro

Nygård

2010

Geoinformatica

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Several representations have been created to store topological information in normal spatial databases. Some work has also been done to represent topology for 3D objects, and such representations could be used to store topology for spatiotemporal objects. However, using 3D models has some disadvantages with regards to retrieving snapshots of the database. This paper aims at creating a spatiotemporal version of the sliced representation that supports efficient retrieval of snapshots of the past and that supports enforcing topological relationships. This paper aims to extend an earlier representation of moving objects so that it can also store and enforce some of the topological relationships between the objects. One use of such a representation is storing a changing spatial partition. As part of the effort to construct the model, an analysis of the topological relationships has been carried out to see which need to be stored explicitly and which can be computed from geometry. Both a basic time slice model and a 3D model are examined to determine how suitable they are for storing topological relationships. An extension of the time slice model is then proposed that solves some of the problems of the basic time slice model. Some algorithms for constructing the new model from snapshots of the objects along with an adjacency graph have been created. The paper also contains a short analysis on how to handle current time, as the time slice model is best at handling historical data, and on ways to speed up searches in a database in which objects of many types are connected to one another and many files therefore potentially need to be accessed.

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“…Similar issues can be observed for conceptual data modelling for multi-representation geo-spatial databases in geographical information systems (Fent et al, 2005;Fonseca et al, 2002;Parent et al, 2006a). An interesting addition for geographic information systems was made explicit by Camossi et al (2003). They elaborated on the requirement for cross-hierarchy conditional information retrieval; for instance, where one has two granular perspectives, one for administrative regions and one for rive sizes, then a realistic query is "if one makes a map with granularity at the Province-level then only rivers with a flow ≥ 10 000 litres/min should be included in the map".…”

Section: Related Workmentioning

confidence: 99%

A Top-Level Categorization of Types of Granularity

Keet

2010

Novel Developments in Granular Computing

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Abstract. Multiple different understandings and uses exist of what granularity is and how to implement it, where the former influences success of the latter with regards to storing granular data and using granularity for automated reasoning over the data or information, such as granular querying for information retrieval. We propose a taxonomy of types of granularity and discuss for each leaf type how the entities or instances relate within its granular level and between levels. Such distinctions give guidelines to a modeler to better distinguish between the types of granularity in the design phase and the software developer to improve on implementations of granularity. Moreover, these foundational semantics of granularity provide a basis from which to develop a comprehensive theory of granularity.

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A multigranular spatiotemporal data model

Cited by 27 publications

References 12 publications

A conceptual view on trajectories

A conceptual view on trajectories

Representing topological relationships for spatiotemporal objects

A Top-Level Categorization of Types of Granularity

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