The importance of locality in the visualization of large datasets

J. M. Brooke, J. Marsh, S. Pettifer, L. S. Sastry

Research output: Contribution to journalArticlepeer-review


Many scientific phenomena in large high-resolution datasets such as the U.K. Ocean Circulation and Advanced Modelling (OCCAM) ocean model are better discovered through visualization than by algorithmic analysis: it is often more straightforward to see a feature than it is to characterize it numerically. Using traditional rendering techniques, the size of modern datasets presents a challenge for even high-end graphical supercomputers, and the cost of such hardware limits its availability for day-to-day analysis. We present an architecture that brings visual analysis to the desktop by exploiting consumer-grade graphics hardware in order to provide initial interactive exploration and Web services to enable finer-grained analysis and interoperability with traditional visualization tools. Copyright © 2006 John Wiley & Sons, Ltd.
Original languageEnglish
Pages (from-to)195-205
Number of pages10
JournalConcurrency and Computation: Practice & Experience
Issue number2
Publication statusPublished - Feb 2007


  • Grid computing
  • Oceanography
  • Visualization
  • Web services


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