Streaming and Data Enrichment

dc.contributor.authorMcDerby, Mary J.en_US
dc.contributor.authorHewitt, William T.en_US
dc.contributor.authorTurner, Martin J.en_US
dc.contributor.editorIk Soo Lim and David Duceen_US
dc.date.accessioned2014-01-31T19:58:16Z
dc.date.available2014-01-31T19:58:16Z
dc.date.issued2007en_US
dc.description.abstractData 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.description.seriesinformationTheory and Practice of Computer Graphicsen_US
dc.identifier.isbn978-3-905673-63-0en_US
dc.identifier.urihttps://doi.org/10.2312/LocalChapterEvents/TPCG/TPCG07/221-228en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectCategories 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 Techniquesen_US
dc.titleStreaming and Data Enrichmenten_US
Files
Original bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
221-228.pdf
Size:
265.3 KB
Format:
Adobe Portable Document Format