Abstract
Multiple granularities are essential to extract significant knowledge from spatiotemporal datasets at different levels of detail. They enable to zoom-in and zoom-out
spatio-temporal datasets, thus enhancing the data modelling flexibility and improving the analysis of information. In this paper we discuss effective solutions to implementation
issues arising when a data model and a query language are enriched with spatio-temporal multigranularity. We propose appropriate representations for space and time dimensions, granularities, granules, and multi-granular values. In particular the design of granularities and their relationships is illustrated with respect to the application of multigranular conversions for data access. Finally, we describe how multigranular spatio-temporal conversions affect data usability and how such important property may be guaranteed. In our discussion, we refer to an existing
multigranular spatio-temporal model, whose design was previously proposed as extension of the ODMG data model.
