https://snicdocs.nsc.liu.se/w/index.php?action=history&feed=atom&title=Scientific_Visualisation_%28Uppsala%2C_Nov_2018%29 2026-04-03T22:28:47Z Revision history for this page on the wiki MediaWiki 1.31.10 https://snicdocs.nsc.liu.se/w/index.php?title=Scientific_Visualisation_(Uppsala,_Nov_2018)&diff=7365&oldid=prev 2020-02-28T09:16:16Z

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Torben Rasmussen (NSC) https://snicdocs.nsc.liu.se/w/index.php?title=Scientific_Visualisation_(Uppsala,_Nov_2018)&diff=7364&oldid=prev 2020-02-28T09:15:01Z

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Torben Rasmussen (NSC) https://snicdocs.nsc.liu.se/w/index.php?title=Scientific_Visualisation_(Uppsala,_Nov_2018)&diff=6930&oldid=prev 2018-09-12T10:11:34Z

<p>Created page with &quot;{{training event info |description=Scientific Visualisation Workshop |fields=Scientific Visualisation |event type=Workshop |location=Uppsala (UPPMAX) |start date=2018-11-26 |end ...&quot;</p> <p><b>New page</b></p><div>{{training event info<br /> |description=Scientific Visualisation Workshop<br /> |fields=Scientific Visualisation<br /> |event type=Workshop<br /> |location=Uppsala (UPPMAX)<br /> |start date=2018-11-26<br /> |end date=2018-11-30<br /> }}<br /> <br /> In collaboration with SeSe, this year's Scientific Visualisation course will be held from 26-th to 30-th of November <br /> in Uppsala, with specially invited guest-lecturer, Alex Telea, who is the author of the course book <br /> &quot;Data Visualization: Principles and Practice&quot; on which the course is based itself.<br /> <br /> The Scientific Visualisation course deals with methods that offer a way to see the unseen, <br /> how to select appropriate methods for a given data set, possibilities and limitations with <br /> methods, and how to use visualisation toolkits. During the course, you will learn to <br /> explore your data interactively in 3D or programmatically using ParaView - an open-source, <br /> multi-platform data analysis and visualisation application. While ParaView platform is <br /> developed for quick build of visualisations and data analysis using qualitative and <br /> quantitative techniques the tool is also well suited for analysis of extremely large <br /> datasets using distributed memory computing resources.<br /> For more information on the content, schedule and how to apply for the course, please <br /> visit the course web page at http://sese.nu/scientific-visualisation-2018<br /> <br /> <br /> Anders Hast - course coordinator<br /> Department of Information Technology<br /> Division of Visual Information and Interaction<br /> anders.hast@it.uu.se</div>

Marcus Holm (UPPMAX)