Abstract
Unrestricted zoom paths are much desired to gain deep understandings during visual analysis of relational databases. We present a multiscale visualization system supporting unrestricted zoom paths. Our system has a flexible visual interface on the client side, called “ZoomTree”, and a powerful and efficient back end with GPU-based parallel online data cubing and CPU-based data clustering. Zoom-trees are seamlessly integrated with a table-based overview using “hyperlinks” embedded in the table, and are designed to represent the entire history of a zooming process that reveals multiscale data characteristics. Arbitrary branching and backtracking in a zoom-tree are made possible by our fast parallel online cubing algorithm for partially materialized data cubes. Partial materialization provides a good tradeoff among preprocessing time, storage and online query time. Experiments and a user study have confirmed the effectiveness of our design.
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Wang, B., Chen, G., Bu, J., Yu, Y. (2011). ZoomTree: Unrestricted Zoom Paths in Multiscale Visual Analysis of Relational Databases. In: Richard, P., Braz, J. (eds) Computer Vision, Imaging and Computer Graphics. Theory and Applications. VISIGRAPP 2010. Communications in Computer and Information Science, vol 229. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25382-9_21
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DOI: https://doi.org/10.1007/978-3-642-25382-9_21
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