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Towards Vague Geographic Data Warehouses

  • Thiago Luís Lopes Siqueira
  • Cristina Dutra de Aguiar Ciferri
  • Valéria Cesário Times
  • Ricardo Rodrigues Ciferri
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7478)

Abstract

Currently, geographic data warehouses provide a means of carrying out spatial analysis together with agile and flexible multidimensional analytical queries over huge volumes of data. However, they do not enable the representation and neither the analysis over real world phenomena that have uncertain locations or vague boundaries, which are denoted by vague spatial objects. In this paper, we introduce the vague geographic data warehouse (vGDW) and its spatially-enabled components at the logical level: attributes, measures, dimensions, hierarchies and queries. We base the vGDW on exact models to represent vague spatial objects. In addition, we combine the fuzzy model with the exact model in relational vGDW to improve the expressiveness of the queries. Finally, a case study is presented to validate our contributions.

Keywords

geographic data warehouse vagueness logical modeling 

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References

  1. 1.
    Malinowski, E., Zimányi, E.: Advanced Data Warehouse Design: From Conventional to Spatial and Temporal Applications. Springer (2008)Google Scholar
  2. 2.
    Bimonte, S., Tchounikine, A., Miquel, M., Pinet, F.: When Spatial Analysis Meets OLAP: Multidimensional Model and Operators. In: Taniar, D., Iwan, L. (eds.) Exploring Advances in Interdisciplinary Data Mining and Analytics, pp. 249–277. IGI (2011)Google Scholar
  3. 3.
    Siqueira, T.L.L., Ciferri, C.D.A., Times, V.C., Ciferri, R.R.: The SB-index and the HSB-Index: efficient indices for spatial data warehouses. Geoinformatica 16(1), 165–205 (2011)CrossRefGoogle Scholar
  4. 4.
    Burrough, P.A., Frank, A.U. (eds.): Geographic Objects with Indeterminate Boundaries. GISDATA, vol. 2. Taylor & Francis (1996)Google Scholar
  5. 5.
    Schneider, M.: Fuzzy Spatial Data Types for Spatial Uncertainty Management in Databases. In: Handbook of Research on Fuzzy Information Processing in Databases, pp. 490–515. IGI (2008)Google Scholar
  6. 6.
    Yuen, S., Tao, Y., Xiao, X., Pei, J.: Superseding Nearest Neighbor Search on Uncertain Spatial Databases. TKDE 22(7), 1041–1055 (2010)Google Scholar
  7. 7.
    Pauly, A., Schneider, M.: VASA: An algebra for vague spatial data in databases. Inf. Syst. 35(1), 111–138 (2010)CrossRefGoogle Scholar
  8. 8.
    Kimball, R., Ross, M.: The Data Warehouse Toolkit, 2nd edn. Wiley (2002)Google Scholar
  9. 9.
    Bejaoui, L., Pinet, F., Schneider, M., Bédard, Y.: OCL for formal modelling of topological constraints involving regions with broad boundaries. GeoInformatica 14(3), 353–378 (2010)CrossRefGoogle Scholar
  10. 10.
    Bejaoui, L., Pinet, F., Bédard, Y., Schneider, M.: Qualified topological relations between spatial objects with possible vague shape. IJGIS 23(7), 877–921 (2009)Google Scholar
  11. 11.
    Cheng, R., Kalashnikov, D.V., Prabhakar, S.: Evaluating Probabilistic Queries over Imprecise Data. In: SIGMOD Conference, pp. 551–562 (2003)Google Scholar
  12. 12.
    Dilo, A., de By, R.A., Stein, A.: A System of Types and Operators for Handling Vague Spatial Objects. IJGIS 21(4), 397–426 (2007)Google Scholar
  13. 13.
    Bittner, T., Stell, J.G.: Vagueness and Rough Location. Geoinformatica 6(2), 99–121 (2002)zbMATHCrossRefGoogle Scholar
  14. 14.
    Worboys, M.: Computation with imprecise geospatial data. Computers, Environmental and Urban Systems 22(2), 85–106 (1998)CrossRefGoogle Scholar
  15. 15.
    Egenhofer, M.J., Franzosa, R.D.: Point-set Topological Spatial Relations. IJGIS 5(2), 161–174 (1991)Google Scholar
  16. 16.
    Harinarayan, V., Rajaraman, A., Ullman, J.D.: Implementing Data Cubes Efficiently. ACM SIGMOD Record 25(2), 205–216 (1996)CrossRefGoogle Scholar
  17. 17.
    Stefanovic, N., Han, J., Koperski, K.: Object-Based Selective Materialization for Efficient Implementation of Spatial Data Cubes. TKDE 12(6), 938–958 (2000)Google Scholar
  18. 18.
    Siqueira, T.L.L., Ciferri, R.R., Times, V.C., Ciferri, C.D.A.: The Impact of Spatial Data Redundancy on SOLAP Query Performance. JBCS 15(2), 19–34 (2009)Google Scholar
  19. 19.
    Siqueira, T.L.L., Mateus, R.C., Ciferri, R.R., Times, V.C., Ciferri, C.D.A.: Querying Vague Spatial Information in Geographic Data Warehouses. In: AGILE Conference, pp. 379–397 (2011)Google Scholar
  20. 20.
    Pourabbas, E., Rafanelli, M.: Characterization of Hierarchies and Some Operators in OLAP environment. In: DOLAP, pp. 54–59 (1999)Google Scholar
  21. 21.
    Mateus, R.C., Times, V.C., Siqueira, T.L.L., Ciferri, R.R., Ciferri, C.D.A.: How Does the Spatial Data Redundancy Affect Query Performance in Geographic Data Warehouses? JIDM 1, 519–534 (2010)Google Scholar
  22. 22.
    Brito, J.J., Siqueira, T.L.L., Times, V.C., Ciferri, R.R., de Ciferri, C.D.: Efficient Processing of Drill-across Queries over Geographic Data Warehouses. In: Cuzzocrea, A., Dayal, U. (eds.) DaWaK 2011. LNCS, vol. 6862, pp. 152–166. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  23. 23.
    Brinkhoff, T., Kriegel, H.P., Schneider, R., Seeger, B.: Multi-step Processing of Spatial. In: ACM SIGMOD Conf., pp. 197–208 (1994)Google Scholar
  24. 24.
    Mohan, P., Wilson, R., Shekhar, S., George, B., Levine, N., Celik, M.: Should SDBMS support a join index?: a case study from CrimeStat. In: ACM GIS, pp. 1–10 (2008)Google Scholar
  25. 25.
    Sampaio, M.C., Souza, A.G., Baptista, C.S.: Towards a Logical Multidimensional Model for Spatial Data Warehousing and OLAP. In: DOLAP, pp. 83–90 (2006)Google Scholar
  26. 26.
    Vaisman, A., Zimányi, E.: A multidimensional model representing continuous fields in spatial data warehouses. In: ACM GIS, pp. 168–177 (2009)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Thiago Luís Lopes Siqueira
    • 1
    • 2
  • Cristina Dutra de Aguiar Ciferri
    • 3
  • Valéria Cesário Times
    • 4
  • Ricardo Rodrigues Ciferri
    • 2
  1. 1.São Paulo Federal Institute of Education, Science and Technology at São CarlosIFSPSão CarlosBrazil
  2. 2.Computer Science DepartmentFederal University of São Carlos, UFSCarSão CarlosBrazil
  3. 3.Computer Science DepartmentUniversity of São Paulo at São Carlos, USPSão CarlosBrazil
  4. 4.Informatics CenterFederal University of Pernambuco, UFPERecifeBrazil

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