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Data Visualization

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chelsi
24 diapositives · 469 Views · Oct 12, 2014

Data Visualization. Lecture 12 Visualization Software Environments: - Overview of Major Systems Distributed and Collaborative Visualization. Visualization Software Environments. IRIS Explorer is one of a family of similar visualization systems

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Data Visualization
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  1. Data Visualization Lecture 12 Visualization Software Environments: - Overview of Major Systems Distributed and Collaborative Visualization

  2. Visualization Software Environments • IRIS Explorer is one of a family of similar visualization systems • AVS, IBM Open Visualization Data Explorer (DX), IRIS Explorer • visual programming based : plug, play, throw away • application decomposed as set of modules, configured at run-time (blur between building and running an application) • open : user can write modules • low-cost

  3. Convergence of Technologies Demand for interactive exploration of large datasets from simulations & measurement Systems made possible late 1980s by: • Visual programming • technology waiting for application - dataflow ideal for visualization because of pipeline • Visualization algorithm development • 3D scalar and vector visualization • Network based window systems • easy to use distributed computing • Faster graphics workstations

  4. AVS • Released 1989 by Stellar as software to help sell graphics workstations • Now software company with range of products: • AVS5, AVS/Express, Gsharp • www.avs.com

  5. IRIS Explorer • Released 1991 by Silicon Graphics, bundled free with every Indigo workstation • Now developed and distributed by NAG Ltd, Oxford • runs on UNIX and Windows • IRIS Explorer Centre of Excellence at Univ of Leeds • www.nag.co.uk • www.comp.leeds.ac.uk/iecoe

  6. IBM Open Visualization Data Explorer – now OpenDX • Released around 1991 by IBM • Made open source in 1999 • www.opendx.org

  7. More recent product Increasing use for medical applications.. .. But also engineering including CFD Marketed by TGS www.tgs.com Amira

  8. vtk is a programming - based toolkit Open source C++ library www.kitware.com vtk - Visualization Toolkit

  9. .. And there are many others http://gd.tuwien.ac.at:8050/D/1/

  10. Distributed and Cooperative Visualization Extending existing systems to new computing developments

  11. Visualize cells where concentration exceeds safety limit Model the dispersion and solve the PDEs… The fugitive pollutant … where is it headed for? Scenario:Release of Toxic Chemical

  12. Traditional data visualization approach is to decompose into: Read in data Construct a visualization as geometry Render the geometry as an image Facilitated by modular visualization environments – such as IRIS Explorer – using concept of dataflow pipeline visualize data render The Starting Point

  13. Traditional approach is: Perform the simulation Perform the visualization Step one visualize data render Simulation Step two Simulation and Visualization

  14. Creating Your Own Modules • It is possible to create your own modules in IRIS Explorer • The mbuilder tool creates a wrapper around your own code • See: www.nag.co.uk/visual/IE/iecbb/DOC/Unix/Doc/MWG/CONTENTS.htm

  15. simulate visualize control render Computational Steering • Greater flexibility is achieved if we integrate the simulation and visualization in the same pipeline • Online control of simulation and visualization • becomes possible in IRIS Explorer through • ability to create own modules

  16. Tracking the Pollution Control: wind direction widget Simulate: finite volume code running as an IRIS Explorer module Visualize: select cells where concentration exceeds threshold Render: draw the cells

  17. Improvements needed • Need to harness external compute resources • Need to bring in wider expertise through collaboration

  18. Select remote host Harnessing Remote Compute Resources Explorer on multiple hosts Explorer on single host • Automatic authentication using: • Globus certificate • SSH Key pair

  19. Simulation Runs Remotely Control: desktop Simulation: remote Cell extraction: remote (so as to minimize network load) Cell filling: local Render: local

  20. Extends the dataflow model to interlink pipelines across the Internet Collaborative server provides the link So one user – for example - can send geometry to another person for viewing render internet Collaborative Data Visualization visualize data render share collaborative server share

  21. It is useful to be able to program the collaboration To adapt to how people want to collaborate To adapt to network bandwidths Here raw data is exchanged so a different visualization can be created visualise render internet Programming the Collaboration visualize data render share collaborative server share

  22. IRIS Explorer COVISA Toolkit

  23. Initiate collaborative session Scientist in lab Link in meteorologist remotely Bring in the Meteorologist Remotely

  24. Data Visualization End of Part 1