Advertisement

Spatial Hierarchies and Topological Relationships in the Spatial MultiDimER Model

  • Elzbieta Malinowski
  • Esteban Zimányi
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3567)

Abstract

In Data Warehouses and On-Line Analytical Processing systems hierarchies are used to analyze high volumes of historical data. On the other hand, the advantage of using spatial data in the analysis process is widely recognized. Therefore, in order to satisfy the growing requirements of decision-making users it is necessary to extend hierarchies for representing spatial data. Based on an analysis of real-world spatial applications, this paper defines different kinds of spatial hierarchies and gives a conceptual representation of them. Further, we study the summarizability problem and classify the topological relationships between hierarchy levels according to the procedures required for ensuring correct measure aggregation.

Keywords

Geographic Information System Hierarchy Level Topological Relationship Spatial Level Measure Aggregation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    ESRI, Inc. ArcGIS data models (2004), http://www.esri.com/software/arcgisdatamodels/index.html
  2. 2.
    Ferri, F., Pourabbas, E., Rafanelli, M., Ricci, F.: Extending geographic databases for a query language to support queries involving statistical data. In: Proc. of the 12th Int. Conf. on Scientific and Statistical Database Management, pp. 220–230 (2000)Google Scholar
  3. 3.
    ISO. SQL multimedia and application packages - part 3: Spatial. Technical report, ISO/IEC FCD 13249-3:2003 (2002) Google Scholar
  4. 4.
    Jensen, C., Klygis, A., Pedersen, T., Timko, I.: Multidimensional data modeling for location-based services. VLDB Journal 13(1), 1–21 (2004)CrossRefGoogle Scholar
  5. 5.
    Kouba, Z., Matoušek, K., Mikšovský, P.: Novel knowledge discovery tools in industrial applications. In: Proc. of the Workshop on Intelligent Methods for Quality Improvement in Industrial Practice, pp. 72–83 (2002)Google Scholar
  6. 6.
    Lenz, H., Shoshani, A.: Summarizability in OLAP and statistical databases. In: Proc. of the 9th Int. Conf. on Scientific and Statistical Database Management, pp. 132–143 (1997)Google Scholar
  7. 7.
    Malinowski, E., Zimányi, E.: OLAP hierarchies: A conceptual perspective. In: Proc. of the 16th Int. Conf. on Advanced Information Systems Engineering, pp. 477–491 (2004)Google Scholar
  8. 8.
    Malinowski, E., Zimányi, E.: Representing spatiality in a conceptual multidimensional model. In: Proc. of the 12th ACM Symposium on Advances in Geographic Information Systems, pp. 12–21 (2004)Google Scholar
  9. 9.
    Microsoft Corporation. SQL Server 2000. Books Online (2003), http://www.microsoft.com/sql/techinfo/productdoc/2000/books.asp
  10. 10.
    Parent, C., Spaccapietra, S., Zimányi, E.: Spatio-temporal conceptual models: Data structures + Space + Time. In: Proc. of the 7th ACM Symposium on Advances in Geographic Information Systems, pp. 26–33 (1999)Google Scholar
  11. 11.
    Pedersen, T., Tryfona, N.: Pre-aggregation in spatial data warehouses. In: Proc. of the 7th Int. Symposium on Advances in Spatial and Temporal Databases, pp. 460–478 (2001)Google Scholar
  12. 12.
    Price, R., Tryfona, N., Jensen, C.: Modeling topological constraints in spatial part-whole relationships. In: Proc. of the 20th Int. Conference on Conceptual Modeling, pp. 27–40 (2001)Google Scholar
  13. 13.
    Stefanovic, N., Han, J., Koperski, K.: Object-based selective materialization for efficient implementation of spatial data cubes. IEEE Trans. on Knowledge and Data Engineering 12(6), 938–958 (2000)CrossRefGoogle Scholar
  14. 14.
    Tryfona, N., Busborg, F., Borch, J.: StarER: A conceptual model for data warehouse design. In: Proc. of the 2nd ACM Int. Workshop on Data Warehousing and OLAP, pp. 3–8 (1999)Google Scholar
  15. 15.
    U.S. Census Bureau. Standard Hierarchy of Census Geographic Entities and Hierarchy of American Indian, Alaska Native, and Hawaiian Entities (2004), http://www.census.gov/geo/www/geodiagram.pdf

Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Elzbieta Malinowski
    • 1
  • Esteban Zimányi
    • 1
  1. 1.Department of Informatics & NetworksUniversité Libre de Bruxelles 

Personalised recommendations