Abstract
In recent years, there has been a large increase in the amount of spatial data obtained from remote sensing, GPS receivers, communication terminals and other domains. Data warehouses help in modeling and mining large amounts of data from heterogeneous sources over an extended period of time. However incorporating spatial data into data warehouses leads to several challenges in data modeling, management and the mining of spatial information. New multidimensional data types for spatial application objects require new OLAP formulations to support query and analysis operations on them. In this paper, we introduce a set of constructs called C 3 for defining data cubes. These include categorization, containment and cubing operations, which present a fundamentally new, user-centric strategy for the conceptual modeling of data cubes. We also present a novel region-hierarchy concept that builds spatially ordered sets of polygon objects and employs them as first class citizens in the data cube. Further, new OLAP constructs to help define, manipulate, query and analyze spatial data have also been presented. Overall, the aim of this paper is to leverage support for spatial data in OLAP cubes and pave the way for the development of a user-centric SOLAP system.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Viswanathan, G., Schneider, M.: BigCube: A MetaModel for Managing Multidimensional Data. In: Proceedings of the 19th Int. Conf. on Software Engineering and Data Engineering (SEDE), pp. 237–242 (2010)
Rivest, S., Bedard, Y., Marchand, P.: Toward Better Support for Spatial Decision Making: Defining the Characteristics of Spatial On-line Analytical Processing (SOLAP). Geomatica-Ottawa 55(4), 539–555 (2001)
Malinowski, E., Zimányi, E.: Representing Spatiality in a Conceptual Multidimensional Model. In: 12th ACM Int. workshop on Geographic Information Systems, pp. 12–22. ACM, New York (2004)
Ferri, F., Pourabbas, E., Rafanelli, M., Ricci, F.: Extending Geographic Databases for a Query Language to Support Queries Involving Statistical Data. In: Int. Conf. on Scientific and Statistical Database Management, pp. 220–230. IEEE, Los Alamitos (2002)
Jensen, C., Kligys, A., Pedersen, T., Timko, I.: Multidimensional Data Modeling for Location-based Services. The VLDB Journal 13(1), 1–21 (2004)
Pedersen, T., Jensen, C., Dyreson, C.: A Foundation for Capturing and Querying Complex Multidimensional Data. Information Systems 26(5), 383–423 (2001)
Viswanathan, G., Schneider, M.: On the Requirements for User-Centric Spatial Data Warehousing and SOLAP. Database Systems for Advanced Applications, 144–155 (2011)
Malinowski, E., Zimányi, E.: Advanced Data Warehouse Design: From Conventional to Spatial and Temporal Applications. Springer, Heidelberg (2008)
Shekhar, S., Chawla, S.: Spatial Databases: A Tour. Prentice Hall, Englewood Cliffs (2003)
Guting, R., Schneider, M.: Realm-based Spatial Data Types: The ROSE algebra. The VLDB Journal 4(2), 243–286 (1995)
Open GIS Consortium: Reference Model, http://openlayers.org (accessed: April 11, 2010)
Schneider, M., Behr, T.: Topological Relationships between Complex Spatial Objects. ACM Transactions on Database Systems (TODS) 31(1), 39–81 (2006)
Chen, T., Khan, A., Schneider, M., Viswanathan, G.: iBLOB: Complex object management in databases through intelligent binary large objects. In: Dearle, A., Zicari, R.V. (eds.) ICOODB 2010. LNCS, vol. 6348, pp. 85–99. Springer, Heidelberg (2010)
Davey, B., Priestley, H.: Introduction to Lattices and Order. Cambridge University Press, Cambridge (2002)
Gray, J., Chaudhuri, S., Bosworth, A., Layman, A., Reichart, D., Venkatrao, M., Pellow, F., Pirahesh, H.: Data cube: A Relational Aggregation Operator Generalizing Group-by, Cross-tab, and Sub-totals. Data Mining and Knowledge Discovery 1(1), 29–53 (1997)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Viswanathan, G., Schneider, M. (2011). OLAP Formulations for Supporting Complex Spatial Objects in Data Warehouses. In: Cuzzocrea, A., Dayal, U. (eds) Data Warehousing and Knowledge Discovery. DaWaK 2011. Lecture Notes in Computer Science, vol 6862. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23544-3_4
Download citation
DOI: https://doi.org/10.1007/978-3-642-23544-3_4
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-23543-6
Online ISBN: 978-3-642-23544-3
eBook Packages: Computer ScienceComputer Science (R0)