Comparative Analysis of State-of-the-Art Spatial Data Warehouse Meta-models - Catching the Expressive Power of SDW Schemas!

Alfredo Cuzzocrea, Robson do N. Fidalgo

Abstract

In this paper we provide a comparative analysis of the Spatial Data Warehouse Metamodel (SDWM) proposal against three state-of-the-art Spatial Data Warehouses (SDW) meta-model proposals. Results of this analysis allow us to conclude that the SDWM proposal exposes a higher expressive power of the comparison approaches, and, in addition to this, it allows us to obtain more concise and compact SDW schemas when compared with the schemas provided by the comparison approaches.

References

  1. Bédard, Y., Merrett, T., & Han, J. 2001. Fundamentals of spatial data warehousing for geographic knowledge discovery. Geographic data mining and knowledge discovery, vol. 2, pp. 53-73.
  2. Del Aguila, P. S. R., Fidalgo, R. N. & Mota, A., 2011. Towards a more straightforward and more expressive metamodel for SDW modeling. In Proceedings of the ACM 14th international workshop on Data Warehousing and OLAP. New York, NY, USA: ACM, pp. 31-36.
  3. Cuzzocrea, A., & Bertino, E., 2011. Privacy Preserving OLAP over Distributed XML Data: A TheoreticallySound Secure-Multiparty-Computation Approach. Journal of Computer and System Sciences 77(6), pp. 965-987.
  4. Cuzzocrea, A., Bertino, E., & Saccà D., 2012. Towards a theory for privacy preserving distributed OLAP. In: EDBT/ICDT Workshops 2012, pp. 221-226.
  5. Cuzzocrea, A. & Fidalgo, R. N., 2012a. Enhancing Coverage and Expressive Power of Spatial Data Warehousing Modeling: The SDWM Approach. In A. Cuzzocrea & U. Dayal, eds. Data Warehousing and Knowledge Discovery. Springer Berlin / Heidelberg, pp. 15-29.
  6. Cuzzocrea, A. & Fidalgo, R. N., 2012b. SDWM: An Enhanced Spatial Data Warehouse Metamodel. In M. Kirikova & J. Stirna, eds. CAiSE Forum. CEURWS.org, pp. 32-39.
  7. Cuzzocrea, A., & Saccà, D., 2012. A Theoretically-Sound Accuracy/Privacy-Constrained Framework for Computing Privacy Preserving Data Cubes in OLAP Environments. In: OTM Conferences 2012, pp. 527- 548.
  8. Fidalgo, R. N. et al., 2004. GeoDWFrame: A Framework for Guiding the Design of Geographical Dimensional Schemas. In Y. Kambayashi, M. Mohania, & W. Wöß, eds. Data Warehousing and Knowledge Discovery. Springer Berlin / Heidelberg, pp. 26-37.
  9. Glorio, O. & Trujillo, J., 2008. An MDA Approach for the Development of Spatial Data Warehouses. In I.-Y. Song, J. Eder, & T. Nguyen, eds. Data Warehousing and Knowledge Discovery. Springer Berlin / Heidelberg, pp. 23-32.
  10. Glorio, O. & Trujillo, J., 2009. Designing Data Warehouses for Geographic OLAP Querying by Using MDA. In O. Gervasi et al., eds. Computational Science and Its Applications - ICCSA 2009. Springer Berlin / Heidelberg, pp. 505-519.
  11. Gray, J. Chaudhuri, S., Bosworth, A., Layman, A., Reichart, D., Venkatrao, M., Pellow, F. & Pirahesh H., 1997. Data Cube: A Relational Aggregation Operator Generalizing Group-by, Cross-Tab, and Sub Totals. Data Mining and Knowledge Discovery 1(1), pp. 29- 53.
  12. Malinowski, E. & Zimányi, E., 2009. Advanced Data Warehouse Design: From Conventional to Spatial and Temporal Applications (Data-Centric Systems and Applications), Springer.
  13. Malinowski, E. & Zimányi, E., 2007. Logical Representation of a Conceptual Model for Spatial Data Warehouses. GeoInformatica, 11(4), pp.431-457.
  14. da Silva, J. et al., 2010. Modelling and querying geographical data warehouses. Information Systems, 35(5), pp.592-614.
  15. Times, Valéria Cesário et al., 2009. A Metamodel for the Specification of Geographical Data Warehouses. In S. Kozielski et al., eds. New Trends in Data Warehousing and Data Analysis. Springer US, pp. 1-22.
  16. Zghal, H. B., Faïz, S. & Ghézala, H. B., 2003. CASME?: A CASE Tool for Spatial Data Marts Design and Generation. In Proceedings of Design and Management of Data Warehouses. Berlin, Germany, pp. 1-11.
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Paper Citation


in Harvard Style

Cuzzocrea A. and do N. Fidalgo R. (2013). Comparative Analysis of State-of-the-Art Spatial Data Warehouse Meta-models - Catching the Expressive Power of SDW Schemas! . In Proceedings of the 15th International Conference on Enterprise Information Systems - Volume 2: ICEIS, ISBN 978-989-8565-60-0, pages 302-309. DOI: 10.5220/0004455903020309


in Bibtex Style

@conference{iceis13,
author={Alfredo Cuzzocrea and Robson do N. Fidalgo},
title={Comparative Analysis of State-of-the-Art Spatial Data Warehouse Meta-models - Catching the Expressive Power of SDW Schemas!},
booktitle={Proceedings of the 15th International Conference on Enterprise Information Systems - Volume 2: ICEIS,},
year={2013},
pages={302-309},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004455903020309},
isbn={978-989-8565-60-0},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 15th International Conference on Enterprise Information Systems - Volume 2: ICEIS,
TI - Comparative Analysis of State-of-the-Art Spatial Data Warehouse Meta-models - Catching the Expressive Power of SDW Schemas!
SN - 978-989-8565-60-0
AU - Cuzzocrea A.
AU - do N. Fidalgo R.
PY - 2013
SP - 302
EP - 309
DO - 10.5220/0004455903020309