The integrated management of both spatial and temporal components of information is crucial in order to extract significant knowledge from datasets concerning phenomena of interest to a large variety of applications. Moreover, multigranularity, i.e., the capability of representing information at different levels of detail, enhances the data modelling flexibility and improves the analysis of information, enabling to zoom-in and zoom-out spatio-temporal datasets. Relying on an existing multigranular spatio-temporal extension of the ODMG data model, in this paper we describe the design of a multigranular spatio-temporal query language. We extend OQL value comparison and object navigation in order to access spatio-temporal objects with attribute values defined at different levels of detail. © 2008 Springer-Verlag Berlin Heidelberg.
CITATION STYLE
Camossi, E., Bertolotto, M., & Bertino, E. (2008). Querying multigranular spatio-temporal objects. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5181 LNCS, pp. 390–403). https://doi.org/10.1007/978-3-540-85654-2_36
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