Adaptive Management of Multigranular Spatio-Temporal Object Attributes

Authors:
Elena Camossi;Elisa Bertino;Giovanna Guerrini;Michela Bertolotto
Affiliations:
School of Computer Science and Informatics, University College Dublin, Belfield, Dublin 4, Ireland;CERIAS - Purdue University, USA;DISI - Università degli Studi di Genova, Genova, Italy 16146;School of Computer Science and Informatics, University College Dublin, Belfield, Dublin 4, Ireland
Venue:
SSTD '09 Proceedings of the 11th International Symposium on Advances in Spatial and Temporal Databases
Year:
2009

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Abstract

In applications involving spatio-temporal modelling, granularities of data may have to adapt according to the evolving semantics and significance of data. In this paper we define ST 2_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 executed at run-time. The event, the condition, and the action may refer to a period of time and a geographical area. The evolution may also be constrained by the attribute values. The ability of dynamically evolving the object attributes results in a more flexible management of multigranular spatio-temporal data but it requires revisiting the notion of object consistency with respect to class definitions and access to multigranular object values. Both issues are formally investigated in the paper.