Multigranular spatio-temporal models: implementation challenges
Abstract
Multiple granularities provide an essential support for extracting significant knowledge from spatio-temporal datasets at different levels of details. They enable to zoom-in and zoom-out spatio-temporal datasets, thus enhancing the data modelling exibility and improving the analysis of information. In this paper we investigate the implementation issues arising when a data model and a query language are enriched with spatio-temporal multigranularity. We introduce appropriate representations for space and time dimensions, granularities, granules, and multi-granular values. Finally, we discuss how multigranular spatio-temporal conversions affect data usability and how such important property may be guaranteed.
Keywords
Logical design, data models, spatial databases
Date of this Version
2008
Comments
GIS '08 Proceedings of the 16th ACM SIGSPATIAL international conference on Advances in geographic information systems