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Data analysis and modern visualization

Data analysis and modern visualization

Visualization is an integral part of the scientific process. As an excellent communication tool used by researchers, it is crucial to make complicated scientific data and relations accessible and understandable. This tutorial will train attendees to expand and develop their visualization skills by providing a “from the ground up” understanding of visualization and its utility in error diagnostic and exploration of data for scientific insight. When used effectively, visualization can provide a complementary and effective toolset for data analysis, which is one of the most challenging problems in many scientific domains. We plan to bridge these gaps by providing attendees with fundamental visualization concepts, execution tools, customization, and usage examples. The tutorial will cover different viewpoints, including (1) a rapid introduction to fundamental visualization concepts, (2) an assay of visualization techniques available accompanied by example application scenarios centered around the VisIt software, (3) scientific data visualization using the Blender software, and (4) combination of visualization of data into advanced animations and videos using a full programming language such as Matlab or Python.

Organizer

  • André Schleife, Department of Materials Science and Engineering, University of Illinois at Urbana-Champaign

Instructors

  • Roberto Reynel Sisneros, National Center for Supercomputing Applications
  • Michael Joseph Waters, Northwestern University
  • Brian Kent, National Radio Astronomy Observatory
  • Colin Ophus, Lawrence Berkeley National Lab