Abstract
In this paper, we investigate the problem of visualizing multidimensional data cubes, and propose a novel technique for supporting advanced OLAP visualization of such data structures. Founding on very efficient data compression solutions for two-dimensional data domains, the proposed technique relies on the amenity of generating “semantics-aware” compressed representation of two-dimensional OLAP views extracted from multidimensional data cubes via the so-called OLAP dimension flattening process. A wide set of experimental results conducted on several kind of synthetic two-dimensional OLAP views clearly confirm the effectiveness and the efficiency of our technique, also in comparison with state-of-the-art proposals.
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.
References
2D, 3D and High-dimensional Data and Information Visualization research group. University of Hannover (2005), available at http://www.iwi.uni-hannover.de/lv/seminar_ss05/bartke/home.htm
Acharya, S., Poosala, V., Ramaswamy, S.: Selectivity Estimation in Spatial Databases. In: Proc. of ACM SIGMOD, pp. 13–24 (1999)
Agrawal, R., Gupta, A., Sarawagi, S.: Modeling Multidimensional Databases. In: Proc. of IEEE ICDE, pp. 232–243 (1997)
Buccafurri, F., Furfaro, F., Saccà, D., Sirangelo, C.: A Quad-Tree Based Multiresolution Approach for Two-Dimensional Summary Data. In: Proc. of IEEE SSDBM, pp. 127–140 (2003)
Bruno, N., Chaudhuri, S., Gravano, L.: STHoles: A Multidimensional Workload-Aware Histogram. In: Proc. of ACM SIGMOD, pp. 211–222 (2001)
Cabibbo, L., Torlone, R.: From a Procedural to a Visual Query Language for OLAP. In: Proc. of IEEE SSDBM, pp. 74–83 (1998)
Chaudhuri, S., Dayal, U.: An Overview of Data Warehousing and OLAP Technology. ACM SIGMOD Record 26(1), 65–74 (1997)
Codd, E.F., Codd, S.B., Salley, C.T.: Providing OLAP to User-Analysts: An IT Mandate. E.F. Codd and Associates TR (1993)
Colliat, G.: OLAP, Relational, and Multidimensional Database Systems. SIGMOD Record 25(3), 64–69 (1996)
Cuzzocrea, A.: Overcoming Limitations of Approximate Query Answering in OLAP. In: Proc. of IEEE IDEAS, pp. 200–209 (2005)
Cuzzocrea, A., Furfaro, F., Saccà, D.: Hand-OLAP: A System for Delivering OLAP Services on Handheld Devices. In: Proc. IEEE ISADS, pp. 80–87 (2003)
Gebhardt, M., Jarke, M., Jacobs, S.: A Toolkit for Negotiation Support Interfaces to Multi-Dimensional Data. In: Proc. of ACM SIGMOD, pp. 348–356 (1997)
Gibbons, P.B., Matias, Y.: New Sampling-Based Summary Statistics for Improving Approximate Query Answers. In: Proc. of ACM SIGMOD, pp. 331–342 (1998)
Gray, J., Chaudhuri, S., Bosworth, A., Layman, A., Reichart, D., Venkatrao, M.: Data Cube: A Relational Aggregation Operator Generalizing Group-By, Cross-Tab, and Sub-Totals. Data Mining and Knowledge Discovery 1(1), 29–53 (1997)
Gunopulos, D., Kollios, G., Tsotras, V.J., Domeniconi, C.: Approximating Multi-Dimensional Aggregate Range Queries over Real Attributes. In: Proc. of ACM SIGMOD, pp. 463–474 (2000)
Hacid, M.-S., Sattler, U.: Modeling Multidimensional Databases: A Formal Object-Centered Approach. In: Proc. of ECIS (1997)
Han, J., Kamber, M.: Data Mining: Concepts and Techniques. Morgan Kaufmann, San Francisco (2000)
Ho, C.-T., Agrawal, R., Megiddo, N., Srikant, R.: Range Queries in OLAP Data Cubes. In: Proc. of ACM SIGMOD, pp. 73–88 (1997)
Inmon, W.H.: Building the Data Warehouse. John Wiley & Sons, Chichester (1996)
Inselberg, A.: Visualization and Knowledge Discovery for High Dimensional Data. In: Proc. of IEEE UIDIS, pp. 5–24 (2001)
Keim, D.A.: Visual Data Mining. Tutorial at VLDB (1997), available at http://www.dbs.informatik.uni-muenchen.de/daniel/VLDBTutorial.ps
Kimball, R.: The Data Warehouse Toolkit. John Wiley & Sons, Chichester (1996)
Koudas, N., Muthukrishnan, S., Srivastava, D.: Optimal Histograms for Hierarchical Range Queries. In: Proc. of ACM PODS, pp. 196–204 (2000)
Lehner, W., Albrecht, J., Wedekind, H.: Normal Forms for Multivariate Databases. In: Proc. of IEEE SSDBM, pp. 63–72 (1998)
Lenz, H.-J., Shoshani, A.: Summarizability in OLAP and Statistical Data Bases. In: Proc. of IEEE SSDBM, pp. 132–143 (1997)
Lenz, H.-J., Thalheim, B.: OLAP Databases and Aggregation Functions. In: Proc. of IEEE SSDBM, pp. 91–100 (2001)
Maniatis, A., Vassiliadis, P., Skiadopoulos, S., Vassiliou, Y.: CPM: A Cube Presentation Model for OLAP. In: Kambayashi, Y., Mohania, M., Wöß, W. (eds.) DaWaK 2003. LNCS, vol. 2737, pp. 4–13. Springer, Heidelberg (2003)
Maniatis, A., Vassiliadis, P., Skiadopoulos, S., Vassiliou, Y.: Advanced Visualization for OLAP. In: Proc. of ACM DOLAP, pp. 9–16 (2003)
Thanh Binh, N., Min Tjoa, A., Wagner, R.: An Object Oriented Multidimensional Data Model for OLAP. In: Lu, H., Zhou, A. (eds.) WAIM 2000. LNCS, vol. 1846, pp. 69–82. Springer, Heidelberg (2000)
Tsois, A., Karayannidis, N., Sellis, T.: MAC: Conceptual Data Modeling for OLAP. Proc. of DMDW (2001), available at http://sunsite.informatik.rwth-aachen.de/Publications/CEUR-WS/Vol-39/paper5.pdf
Vassiliadis, P.: Modeling Multidimensional Databases, Cubes and Cube Operations. In: Proc. of IEEE SSDBM, pp. 53–62 (1998)
Vitter, J.S., Wang, M., Iyer, B.: Data Cube Approximation and Histograms via Wavelets. In: Proc. of ACM CIKM, pp. 96–104 (1998)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2006 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Cuzzocrea, A., Saccà, D., Serafino, P. (2006). A Hierarchy-Driven Compression Technique for Advanced OLAP Visualization of Multidimensional Data Cubes. In: Tjoa, A.M., Trujillo, J. (eds) Data Warehousing and Knowledge Discovery. DaWaK 2006. Lecture Notes in Computer Science, vol 4081. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11823728_11
Download citation
DOI: https://doi.org/10.1007/11823728_11
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-37736-8
Online ISBN: 978-3-540-37737-5
eBook Packages: Computer ScienceComputer Science (R0)