Surround-screen projection-based virtual reality: the design and implementation of the CAVE
SIGGRAPH '93 Proceedings of the 20th annual conference on Computer graphics and interactive techniques
VisDB: a system for visualizing large databases
SIGMOD '95 Proceedings of the 1995 ACM SIGMOD international conference on Management of data
An overview of data warehousing and OLAP technology
ACM SIGMOD Record
VIS '97 Proceedings of the 8th conference on Visualization '97
Data mining: concepts and techniques
Data mining: concepts and techniques
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ICDE '96 Proceedings of the Twelfth International Conference on Data Engineering
On the Computation of Multidimensional Aggregates
VLDB '96 Proceedings of the 22th International Conference on Very Large Data Bases
Recursive Pattern: A Technique for Visualizing Very Large Amounts of Data
VIS '95 Proceedings of the 6th conference on Visualization '95
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UIDIS '01 Proceedings of the Second International Workshop on User Interfaces to Data Intensive Systems (UIDIS'01)
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VIS '90 Proceedings of the 1st conference on Visualization '90
Towards a Novel OLAP Interface for Distributed Data Warehouses
DaWaK '01 Proceedings of the Third International Conference on Data Warehousing and Knowledge Discovery
DocCube: multi-dimensional visualisation and exploration of large document sets
Journal of the American Society for Information Science and Technology
Interactive visual exploration of association rules with rule-focusing methodology
Knowledge and Information Systems
Visual Data Mining in Immersive Virtual Environment Based on 4K Stereo Images
VMR '09 Proceedings of the 3rd International Conference on Virtual and Mixed Reality: Held as Part of HCI International 2009
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This paper presents a flexible system, DIVE-ON, for the purpose of visual data mining. A new approach to interactively visualize and explore N-dimensional data warehouses in an immersed virtual environment is put forth. DIVE-ON is capable of constructing a multidimensional data model on a remote system, transporting pertinent views to a CAVE, creating an immersed virtual environment and providing an interactive data mining toolset. DIVE-ON architecture emphasizes the development of two independent subsystems, a visualization environment and a virtual data warehouse. The first objective of our research is to examine the possibility of effective mining, and manipulating views with little or no instructional help by providing an environment that is built around the human's visual, sensorimotor, and spatial knowledge acquisition abilities. The second goal is to create a highly transparent and centralized data warehouse that integrates various distributed data sources. Within the warehouse, DIVE-ON incorporates an XML-based multidimensional query language (XMDQL) to circulate the queries among the distributed data sources.