Abstract
We present a framework for visualizing remote distributed data sources using a multi-user immersive virtual reality environment. DIVE-ON is a system prototype that consolidates distributed data sources into a multidimensional data model, transports user-specified views to a 3D immersive display, and presents various data attributes and mining results as virtual objects in true 3D interactive virtual reality. In this environment, the user navigates through data by walking or flying, and interacts with its objects simply by “reaching out” for them. To support large sets of data while maintaining an interactive frame rate we propose the VOLAP-tree. This data structure is well suited for indexing both levels of abstraction and decomposition of the virtual world. The DIVE-ON architecture emphasizes the development of two main independent units the visualization application the centralized virtual data warehouse Unlike traditional desktop decision support systems, virtual reality enables DIVE-ON to exploit natural human sensorimotor and spatial pattern recognition skills to gain insight into the significance of data.
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
Ammoura, A., Zaïane, O.R., and Ji, Y., “Immersed Visual Data Mining: Walking the Walk,” Proc. 18th British National Conference on Databases (BNCOD’01), Oxford, 2001.
Agarwal S., Agrawal R., Deshpande P., Gupta A., Naughton J.F., Ramakrishnan R. and Sarawagi S., “On the Computation of Multidimensional Aggregates,” Proc. of VLDB Conference, 1996, pp 506–521.
Baker, M.P., “Human Factors in Virtual Environments for the Visual Analysis of Scientific Data,” NCSA Publications: National Centre for Supercomputer Applications.
Chaudhuri, S., and Umeshwar, D., “An Overview of Data Warehousing and OLAP Technology,” Proc. ACM SIGMOD Record, March, 1997.
DeFanti, T.A., Cruz-Neira, C., and Sandin, D.J., “Surround-Screen Projection-Based Virtual Reality: The Design and Implementation of the CAVE,” Proceedings of ACM SIGGRAPH, 1993, http://www.evl.uic.edu/EVL/VR/systems.shtml.
Foley J. and Ribarsky, B., “Next-Generation Data Visualization Tools.” In Scientific Visualization Advances and Challenges, chapter 7, pp 103–127. Academic Press/IEEE Computer Society Press, San Diego, CA, 1994.
Gary, J., Chaudhuri, S., Bosworth, A., Layman, A., Reichart, D., and Venkatrao, M., “Data Cube: A Relational Aggregation Operator Generalizing Group-by, Cross-Tab, and Sub-Totals,” Proc. of the Twelfth IEEE International Conference on Data Engineering, February, 1996, pp 152–159.
Green, M. and Shaw, C. develop MR-Toolkit at the University of Alberta: http://www.cs.ualberta.ca/~graphics/MRToolkit.html
Han J., and Kamber M., “Data Mining: Concepts and Techniques,” Morgan Kaufmann Publishers, 2001.
Hand, C., “A Survey of 3D Interaction Techniques,” Computer Graphics Forum, December, 1997, 16(5), pp 269–281.
Jaswal, V., “CAVEvis: Distributed Real-Time Visualization of Time-Varying Scalar and Vector Fields Using the CAVE Virtual Reality Theater,” IEEE Visualization, 1997, pp 301–308.
Keim D.A., Kriegel H.-P.: VisDB: A System for Visualizing Large Databases, System Demonstration, Proc. ACM SIGMOD Int. Conf. on Management of Data, San Jose, CA, 1995.
Pilot Software: http://www.pilotsw.com/news/olapwhite.htm
van Dam, A., Forsberg, A.S., Laidlaw, D.H., LaViola J.J., and Simpson, R.M., “Immersive VR for Scientific Visualization: A Progress Report,” Proc. IEEE Virtual Reality, March, 2000 (VR2000).
Ward, M.O., Keim D.A.: Screen Layout Methods for Multidimensional Visualization, Euro-American Workshop on Visualization of Information and Data, 1997.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2001 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Ammoura, A., Zaïane, O., Goebel, R. (2001). Towards a Novel OLAP Interface for Distributed Data Warehouses. In: Kambayashi, Y., Winiwarter, W., Arikawa, M. (eds) Data Warehousing and Knowledge Discovery. DaWaK 2001. Lecture Notes in Computer Science, vol 2114. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44801-2_18
Download citation
DOI: https://doi.org/10.1007/3-540-44801-2_18
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-42553-3
Online ISBN: 978-3-540-44801-3
eBook Packages: Springer Book Archive