A DATA WAREHOUSE ARCHITECTURE FOR INTEGRATING FIELD-BASED DATA

Alberto Salguero, Francisco Araque, Ramón Carrasco

2007

Abstract

Spatial DataWarehouses (SDWs) combine DWs and Spatial Data Bases (SDBs) for managing significant amounts of historical data that include spatial location. Some spatial information can be seen as a continuous field, and the information of interest is obtained at each point of a space. The previously proposed extensions of the multidimensional data model, used in Data Warehousing, only deal with spatial objects. None of them consider field-based information. This paper presents a Data Warehouse architecture that automatically determines the best parameters for refreshing and integrating field-based data from different data sources.

References

  1. Araque, F., Salguero, A., Abad, M.M., 2006b. Application of data warehouse and Decision Support System in Soaring site recommendation. Proc. Information and Communication Technologies in Tourism, ENTER. Springer Verlag, Lausanne, Switzerland.
  2. Araque, F., Salguero, A.G., Delgado, C., Garvi, E., Samos, J., 2006a. Algorithms for integrating temporal properties of data in Data Warehouse. 8th International Conference on Enterprise Information Systems (ICEIS). Paphos, Cyprus.
  3. Araque, F., Samos, J., 2003. Data warehouse refreshment maintaining temporal consistency. 5th Intern. Conference on Enterprise Information Systems, ICEIS. Angers. France.
  4. Bédard, Y., T. Merrett and J. Han. 2001. Fundamentals of spatial data warehousing for geographic knowledge discovery. Geographic Data Mining and Knowledge Discovery. Ed. H. Miller & J. Han, Taylor & Francis.
  5. Bimonte, S., Tchounikine, A., Miquel, M., 2005. Towards a Spatial Multidimensional Model , DOLAP05, ACM Eighth International Workshop on Data Warehousing and OLAP , Bremen, Germany.
  6. Gascueña, C. M., Cuadra, C., Martínez, P. A., 2006. Multidimensional approach to the representation of the spatio-temporal multi-granularity. In proceedings of the Intern. Conference on Enterprise Information Systems (ICEIS). Paphos, Cyprus.
  7. Inmon, W.H., 2002. Building the Data Warehouse. John Wiley.
  8. Malinowski, E., Zimányi, E., 2004. Representing spatiality in a conceptual multidimensional model. In proceedings of the 12th annual ACM International workshop on Geographic information systems. Washington DC, New York, USA.
  9. Sheth, A., Larson, J., 1990. Federated Database Systems for Managing Distributed, Heterogeneous and Autonomous Databases. ACM Computing Surveys, Vol. 22, No. 3
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Paper Citation


in Harvard Style

Salguero A., Araque F. and Carrasco R. (2007). A DATA WAREHOUSE ARCHITECTURE FOR INTEGRATING FIELD-BASED DATA . In Proceedings of the Ninth International Conference on Enterprise Information Systems - Volume 1: ICEIS, ISBN 978-972-8865-88-7, pages 577-580. DOI: 10.5220/0002391105770580


in Bibtex Style

@conference{iceis07,
author={Alberto Salguero and Francisco Araque and Ramón Carrasco},
title={A DATA WAREHOUSE ARCHITECTURE FOR INTEGRATING FIELD-BASED DATA},
booktitle={Proceedings of the Ninth International Conference on Enterprise Information Systems - Volume 1: ICEIS,},
year={2007},
pages={577-580},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002391105770580},
isbn={978-972-8865-88-7},
}


in EndNote Style

TY - CONF
JO - Proceedings of the Ninth International Conference on Enterprise Information Systems - Volume 1: ICEIS,
TI - A DATA WAREHOUSE ARCHITECTURE FOR INTEGRATING FIELD-BASED DATA
SN - 978-972-8865-88-7
AU - Salguero A.
AU - Araque F.
AU - Carrasco R.
PY - 2007
SP - 577
EP - 580
DO - 10.5220/0002391105770580