TOWARDS DATA WAREHOUSES FOR NATURAL HAZARDS

Hicham Hajji, Mohand-Said Hacid, Hassan Badir

2005

Abstract

Data warehousing has emerged as an effective technique for converting data into useful information. It is an improved approach to integrate data from multiple, often very large, distributed, heterogeneous databases and other information sources. This paper examines the possibility of using data warehousing techniques in the natural hazards management framework to integrate various functional and operational data which are usually scattered across multiple, dispersed and fragmented systems. We present a conceptual data model for the data warehouse in the presence of various data formats such as geographic and multimedia data. We propose OLAP operations for browsing information in the data warehouse.

References

  1. Theodoratos, D., and Sellis, T. 1999. Design data warehouse In Data and Knowledge Engineering, Vol. 31, pp. 279-301.
  2. Adriaans P. and D. Zantinge. 1996. Data Mining, Addison Wesley Longman Limited, Reading, Massachusetts.
  3. J. Widom, 1995. Research problems in data warehousing, In Proc the Int. Conf. on Information and Knowledge Management pages 25- 26 Baltimore, Maryland.
  4. J. Han, K. Koperski and N. Stefanovi, 1997. GeoMiner: A system prototype for spatial data mining. In Proc. 1997 ACM SIGMOD Int Conf Management of Data pages 553 - 556 Tucson Arizona.
  5. Han J., Stefanovic N., and Koperski K., 1998. Selective Materialization: An Efficient Method for Spatial Data Cube Construction. In Pacific-Asia Conf. on Knowledge Discovery and Data mining, PAKDD.
  6. Stefanovic N., Han J., and Koperski K., 2000. ObjectBased Selective Materialization for Efficient Implementation of Spatial Data Cubes. In IEEE Transactions on Knowledge and Data Engineering (TKDE), 12(6).
  7. Bédard Y., Merrett T., Han J., 2001, Fundaments of Spatial Data Warehousing for Geographic Knowledge Discovery. In Miller H. and Han J. (eds.) Geographic Data Mining and knowledge discovery. Taylor & Francis.
  8. Shekhar S., Lu C.T., Tan S., Chawla S. and Vatsavai R.R., 2001, Map cube: a visualization tool for spatial data warehouses. In Miller H., Han J. (eds.) Geographic Data Mining and Knowledge Discovery. Taylor & Francis.
  9. Kimbal R, 1996, The Data Warehouse Toolkit. John Wiley & Sons.
  10. J. Gray. S. Chaudhuri, A Bosworth, 1997, Data cube: A relational aggregation operator generalizing groupby crosstab and subtotals Data Mining and Knowledge Discovery, 29-54.
Download


Paper Citation


in Harvard Style

Hajji H., Hacid M. and Badir H. (2005). TOWARDS DATA WAREHOUSES FOR NATURAL HAZARDS . In Proceedings of the Seventh International Conference on Enterprise Information Systems - Volume 1: ICEIS, ISBN 972-8865-19-8, pages 415-419. DOI: 10.5220/0002519704150419


in Bibtex Style

@conference{iceis05,
author={Hicham Hajji and Mohand-Said Hacid and Hassan Badir},
title={TOWARDS DATA WAREHOUSES FOR NATURAL HAZARDS},
booktitle={Proceedings of the Seventh International Conference on Enterprise Information Systems - Volume 1: ICEIS,},
year={2005},
pages={415-419},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002519704150419},
isbn={972-8865-19-8},
}


in EndNote Style

TY - CONF
JO - Proceedings of the Seventh International Conference on Enterprise Information Systems - Volume 1: ICEIS,
TI - TOWARDS DATA WAREHOUSES FOR NATURAL HAZARDS
SN - 972-8865-19-8
AU - Hajji H.
AU - Hacid M.
AU - Badir H.
PY - 2005
SP - 415
EP - 419
DO - 10.5220/0002519704150419