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.

REFERENCES

• 1: T. C. Bailey and A. C. Gatrell. Interactive Spatial Data Analysis, Second Edition. Longman, 1995.
• 2: S. Balley, C. Parent, and S. Spaccapietra. Modelling Geographic Data with Multiple Representations. International Journal of Geographical Information Science, 18(4):327--352, 2004.
• 3: Claudio Bettini , Sushil G. Jajodia , Sean X. Wang, Time Granularities in Databases, Data Mining and Temporal Reasoning, Springer-Verlag New York, Inc., Secaucus, NJ, 2000
• 4: Claudio Bettini , X. Sean Wang , Sushil Jajodia, Temporal Semantic Assumptions and Their Use in Databases, IEEE Transactions on Knowledge and Data Engineering, v.10 n.2, p.277-296, March 1998 [doi>10.1109/69.683757]
• 5: E. Camossi, M. Bertolotto, and E. Bertino. A multigranular Object-oriented Framework Supporting Spatio-temporal Granularity Conversions. International Journal of Geographical Information Science, 20(5):511--534, 2006.
• 6: Curtis E. Dyreson , William S. Evans , Hong Lin , Richard Thomas Snodgrass, Efficiently Supporting Temporal Granularities, IEEE Transactions on Knowledge and Data Engineering, v.12 n.4, p.568-587, July 2000 [doi>10.1109/69.868908]
• 7: C. S. Jensen, C. E. Dyreson, M. Bohlen, J. Clifford, and al. A Consensus Glossary of Temporal Database Concepts. In O. Etzion, S. Jajodia, and S. Sripada, editors, Temporal Databases: Research and Practice, number 1399 in Lecture Notes in Computer Science, pages 366--405. Springer-Verlag, 1998.
• 8: Vijay Khatri , Sudha Ram , Richard Thomas Snodgrass , Grady M. O'Brien, Supporting User-Defined Granularities in a Spatiotemporal Conceptual Model, Annals of Mathematics and Artificial Intelligence, v.36 n.1-2, p.195-232, September 2002 [doi>10.1023/A:1015868307494]
• 9: Jun Yang , Jennifer Widom, Incremental Computation and Maintenance of Temporal Aggregates, Proceedings of the 17th International Conference on Data Engineering, p.51-60, April 02-06, 2001

INDEX TERMS

Primary Classification:
  H. Information Systems
  H.2 DATABASE MANAGEMENT
      H.2.1 Logical Design
          Subjects: Data models

Additional Classification:
  H. Information Systems
  H.2 DATABASE MANAGEMENT
      H.2.8 Database applications
          Subjects: Spatial databases and GIS

Keywords:
multirepresentation, multiresolution, spatial and temporal granularities, spatio-temporal databases