Streaming and Data Enrichment
dc.contributor.author | McDerby, Mary J. | en_US |
dc.contributor.author | Hewitt, William T. | en_US |
dc.contributor.author | Turner, Martin J. | en_US |
dc.contributor.editor | Ik Soo Lim and David Duce | en_US |
dc.date.accessioned | 2014-01-31T19:58:16Z | |
dc.date.available | 2014-01-31T19:58:16Z | |
dc.date.issued | 2007 | en_US |
dc.identifier.isbn | 978-3-905673-63-0 | en_US |
dc.identifier.uri | http://dx.doi.org/10.2312/LocalChapterEvents/TPCG/TPCG07/221-228 | en_US |
dc.description.abstract | Data is being created at a continuously increasing rate. Scientists are drowning in their data . So much so they cannot visualize the data to see the big picture. This work-in-progress paper describes a data capture and visualization problem, and the steps being undertaken to solve the problem. An overview is given of the various approaches to dealing with these large data sets that have been previously proposed and the application of such methods within a well known scientific visualization tool. The paper then goes on to propose a method that deals with large data visualization by addressing the bottlenecks in the visualization pipeline, and combining some of the approaches described herein with parallel techniques on a high performance visualization system. | en_US |
dc.publisher | The Eurographics Association | en_US |
dc.subject | Categories and Subject Descriptors (according to ACM CCS): I.3.3 [Computer Graphics]: Picture/Image Generation I.3.4 [Computer Graphics]: Graphics Utilities I.3.5 [Computer Graphics]: Computational Geometry and Object Modelling I.3.6 [Computer Graphics]: Methodology and Techniques | en_US |
dc.title | Streaming and Data Enrichment | en_US |
dc.description.seriesinformation | Theory and Practice of Computer Graphics | en_US |
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EG UK Theory and Practice of Computer Graphics 2007
ISBN 978-3-905673-63-0