Time Granularities in Databases, Data Mining and Temporal Reasoning
Time Granularities in Databases, Data Mining and Temporal Reasoning
Supporting User-Defined Granularities in a Spatiotemporal Conceptual Model
Annals of Mathematics and Artificial Intelligence
Temporal Semantic Assumptions and Their Use in Databases
IEEE Transactions on Knowledge and Data Engineering
Efficiently Supporting Temporal Granularities
IEEE Transactions on Knowledge and Data Engineering
Incremental Computation and Maintenance of Temporal Aggregates
Proceedings of the 17th International Conference on Data Engineering
Adaptive Management of Multigranular Spatio-Temporal Object Attributes
SSTD '09 Proceedings of the 11th International Symposium on Advances in Spatial and Temporal Databases
Multi-granular spatio-temporal object models: concepts and research directions
ICOODB'09 Proceedings of the Second international conference on Object databases
Providing multi-scale consistency for multi-scale geospatial data
Proceedings of the 25th International Conference on Scientific and Statistical Database Management
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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.