Adaptive management of multigranular spatio-temporal object attributes

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Title: Adaptive management of multigranular spatio-temporal object attributes
Authors: Camossi, Elena
Bertino, Elisa
Guerrini, Giovanna
Bertolotto, Michela
Permanent link: http://hdl.handle.net/10197/1606
Date: 8-Apr-2009
Abstract: In applications involving spatio-temporal modelling, granularities of data may have to adapt according to the evolving semantics and significance of data. To address such a problem, in this paper we define ST2 ODMGe, a multigranular spatio-temporal model supporting evolutions, which encompass the dynamic adaptation of attribute granularities, and the deletion of attribute values. Evolutions are specified as Event - Condition - Action rules and are performed at run-time. The event, the condition and the action may refer to a period of time and a geographical area. Periodic evolutions may be specified, referring to both transaction and valid time dimensions. The evolution may also be constrained by the attribute values. Evolutions greatly enhance flexibility in multigranular spatio-temporal data handling but require revisiting the notion of object consistency with respect to class definitions and access to multigranular object values.
Funding Details: Science Foundation Ireland
Irish Research Council for Science, Engineering & Technology
Type of material: Technical Report
Publisher: Purdue University. Center for Education and Research in Information Assurance and Security
Subject LCSH: Object-oriented methods (Computer science)
Granular computing
Language: en
Status of Item: Not peer reviewed
Appears in Collections:Computer Science Research Collection

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