Skip to main content
SpringerLink
Log in

Querying Vague Spatial Information in Geographic Data Warehouses

  • Chapter
  • First Online:
Advancing Geoinformation Science for a Changing World

Part of the book series: Lecture Notes in Geoinformation and Cartography ((LNGC,volume 1))

Abstract

Non-redundant geographic data warehouse (GDW) schemas have been recognized as an essential issue in the GDW design. However, little attention has been devoted to the study of how the handling of vague spatial data affects query performance and storage requirements in GDW. In this paper we investigate the query processing performance over nonredundant GDW schemas that are based on different spatial representation approaches for handling spatial data uncertainty. Further, we analyze the indexing issue, aiming at improving query performance on a nonredundant GDW with vague spatial data. We concluded that the adaptation of an existing index for GDW aiming at handling uncertain spatial data does not satisfy completely the performance requirements. Therefore, there is a need for new index structures for processing vague objects in GDW.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 219.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  • Ciferri, C. D., Ciferri, R. R., Forlani, D. T., Traina, A. J., and Souza, F. F. (2007). Horizontal Fragmentation as a Technique to Improve the Performance of Drill-down and Roll-up Queries. ACM SAC (pp. 494–499).

    Google Scholar 

  • Cobb, M.A., Petry, F.E., Shaw, K.B. (2000). Fuzzy spatial relationship refinements based on minimum bounding rectangles variations. Fuzzy Sets and Systems,v.113 (1), 111–120.

    Google Scholar 

  • Cohn, A. G., and Gotts, N. M. (1996). The Egg-yolk Representation of Regions with Indeterminate Boundaries. In: P. A. Burrough, and A. U. Frank, Geographic Objects with Indeterminate Boundaries - GISDATA 2 (pp. 171–187).

    Google Scholar 

  • David, P., Somodevilla, M. J., and Pineda, I. H. (2007). Fuzzy Spatial Data Warehouse: A Multidimensional Model. 8th Mexican International Conference on Current Trends in Computer Science (pp. 3–9).

    Google Scholar 

  • Dilo, A., By, R.A., Stein, A. (2007). A system of types and operators for handling vague spatial objects. IJGIS 21(4), 397–426.

    Google Scholar 

  • Egenhofer, M. J., and Franzosa, R. D. (1991). Point-set Topological Spatial Relations. IJGIS, (5), 161–174.

    Google Scholar 

  • Fasel, D., and Shahzad, K. (2010). A DataWarehouse Model for Integrating Fuzzy Concepts in Meta Table Structures. 17th IEEE International Conference and Workshops on Engineering of Computer Based Systems, (pp. 100–109).

    Google Scholar 

  • Ferreira, A. C., Campos, M. L., and Tanaka, A. (2001). An Architecture for Spatial and Dimensional Analysis Integration. World Multiconference on Systemics, Cibernetics and Informatics. Volume XIV - Computer Science and Engineering. Part II.

    Google Scholar 

  • Freundschuh, S. M. (1992). Is There a Relationship between Spatial Cognition and Environmental Patterns? International Conference GIS (pp. 288–304). Pisa, Italy: Springer-Verlag.

    Google Scholar 

  • Furtado, P. (2004). Experimental Evidence on Partitioning in Parallel Data Warehouses. 7th ACM DOLAP, (pp. 23–30).

    Google Scholar 

  • Kalashnikov, D., Ma, Y., Mehrotra, S., Hariharan, R. (2006). Index for fast retrieval of uncertain spatial point data. In: ACM GIS 2006, Arlington, USA, pp. 195–202.

    Google Scholar 

  • Kimball, R. and Ross, M. (2002) The Data Warehouse Toolkit. Wiley, 2nd ed. Li, R., Bhanu, B., Ravishankar, C., Kurth, M., and Ni, J. (2007). Uncertain Spatial Data Handling: Modeling, Indexing and Query. Computers and Geosciences, (33), 42–61.

    Google Scholar 

  • Malinowski, E., and Zimányi, E. (2008). Advanced Data Warehouse Design: From Conventional to Spatial and Temporal. (Data-Centric Systems and Applications): Springer Publishing Company, Inc.

    Google Scholar 

  • Mark, D. M., and Egenhofer, M. J. (1994). Modeling Spatial Relations between Lines and Regions: Combining Formal Mathematical Models and Human Subject Testing. Cartography and Geographic Information Systems, 21(3), 195–212.

    Google Scholar 

  • Mateus, R. C., Times, V. C., Siqueira, T. L., Ciferri, R. R., and Ciferri, C. D. (2010). How Does the Spatial Data Redundancy Affect Query Performance in Geographic Data Warehouses?. JIDM, v. 1, pp. 519–534, 2010.

    Google Scholar 

  • O'Neil, P., Graefe, G. (1995) “Multi-table joins through bitmapped join indices,” In: ACM SIGMOD Record, v.24, n.3, pp. 8–11.

    Article  Google Scholar 

  • O’Neil, P., O’Neil, E., Chen, X., and Revilak, S. (2009). The Star Schema Benchmark and Augmented Fact Table Indexing. TPCTC’2009, pp. 237–252.

    Google Scholar 

  • Oman, C. (1996). GIS and the Channel Tunnel Rail Link. Institution of Civil Engineers, Geographic Information Systems, (pp. 19–22).

    Google Scholar 

  • Petry, F.E., Ladner, R. and Somodevilla, M. (2007). Indexing implementation for vague spatial regions with R-trees and Grid Files. A. Morris and S. Kokhan (Eds.) Geographic Uncertainty in Environmental Security. Springer, pp.187-199.

    Google Scholar 

  • Randell, D. A., and Cohn, A. G. (1989). Modelling Topological and Metrical Properties in Physical Processes. In: H. Levesque, R. Brachmann, and R. Reiter, Principles of Knowledge Representation and Reasoning. pp. 55–66.

    Google Scholar 

  • Randell, D. A., Cui, Z., and Cohn, A. G. (1992). A Spatial Logic based on Regions and Connection. 3rd International Conference on Principles of Knowledge Representation and Reasoning.

    Google Scholar 

  • Rao, F., Zhang, L., Yu, X., Li, Y. and Chen, Y. (2003) Spatial hierarchy and OLAPfavored search in spatial data warehouse. 6th ACM DOLAP, pp. 48–55.

    Google Scholar 

  • Sapir, L., Shmilovici, A., and Rokach, L. (2008). A Methodology for the Design of a Fuzzy Data Warehouse. 4th International IEEE Conference on Intelligent Systems, pp. 2–14 - 2–21.

    Google Scholar 

  • Sharma, J., Flewelling, D. M., and Egenhofer, M. J. (1994). A Qualitative Spatial Reasoner. 6th International Symposium on Spatial Data Handling, (pp. 665–681). Edinburgh, Scotland.

    Google Scholar 

  • Siqueira, T. L., Ciferri, R. R., Times, V. C., and Ciferri, C. D. (2009). The Impact of Spatial Data Redundancy on SOLAP Query Performance. JBCS, 15 (2), 19–34.

    Google Scholar 

  • Somodevilla, M. and Petry, F.E. (2004). Indexing Mechanisms to Query FMBRs. NAFIPS’2004, pp. 198–202.

    Google Scholar 

  • Times, V. C., Fidalgo, R. N., Fonseca, R., Silva, J., and Oliveira, A. G. (2008). A Metamodel for the Specification of Geographical Data warehouses. Annals of Information Systems, (5), 93–114.

    Google Scholar 

  • Yuen, S., Tao, Y, Xiao, X., Pei, J. (2010) Superseding Nearest Neighbor Search on Uncertain Spatial Databases. IEEE TKDE, v. 22, n. 7, pp. 1041–1055.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. São Paulo Federal Institute of Education, Science and Technology, IFSP, São Carlos, Brazil

    Thiago Luís Lopes Siqueira

  2. Computer Science Department, Federal University of São Carlos, UFSCar, São Carlos, Brazil

    Thiago Luís Lopes Siqueira & Ricardo Rodrigues Ciferri

  3. Informatics Center, Federal University of Pernambuco, UFPE, Recife, Brazil

    Rodrigo Costa Mateus & Valéria Cesário Times

  4. Computer Science Department, University of São Paulo at São Carlos, USP, São Carlos, Brazil

    Cristina Dutra Aguiar de Ciferri

Authors
  1. Thiago Luís Lopes Siqueira
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Rodrigo Costa Mateus
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Ricardo Rodrigues Ciferri
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Valéria Cesário Times
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Cristina Dutra Aguiar de Ciferri
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Thiago Luís Lopes Siqueira .

Editor information

Editors and Affiliations

  1. , Faculty of Geosciences, University of Utrecht, Utrecht, 3508, Netherlands

    Stan Geertman

  2. , Institut für Angewandte Informatik, UniBw München, Neubiberg, 85577, Germany

    Wolfgang Reinhardt

  3. Utrecht University, Heidelberglaan 2, Utrecht, 3584, Netherlands

    Fred Toppen

Rights and permissions

Reprints and permissions

Copyright information

© 2011 Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

Siqueira, T.L.L., Mateus, R.C., Ciferri, R.R., Times, V.C., de Ciferri, C.D.A. (2011). Querying Vague Spatial Information in Geographic Data Warehouses. In: Geertman, S., Reinhardt, W., Toppen, F. (eds) Advancing Geoinformation Science for a Changing World. Lecture Notes in Geoinformation and Cartography(), vol 1. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-19789-5_19

Download citation

Publish with us

Policies and ethics

Search

Navigation