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DTSTART:19700308T020000
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DTSTAMP:20260724T151407Z
LOCATION:Bldg. 6 - 102
DTSTART;TZID=Europe/Stockholm:20260630T134500
DTEND;TZID=Europe/Stockholm:20260630T154500
UID:submissions.pasc-conference.org_PASC26_sess127@linklings.com
SUMMARY:MS3D - Impactful Scientific Visualization
DESCRIPTION:Access the recording\n\nOrganizer(s): Guillermo Marin (Barcelo
 na Supercomputing Center, Universitat Autònoma de Barcelona), and Guillaum
 e Houzeaux (Barcelona Supercomputing Center)\n\nData visualization is a po
 werful means of exploring data and communicating complex information to di
 verse audiences, both expert and non-expert. Although widely used by scien
 tists and researchers, it often remains confined to self-exploration and p
 eer communication within specialized fields. Moreover, the use of data vis
 ualization for communication purposes is often overlooked. However, advanc
 ed visualization tools and techniques can be leveraged across disciplines 
 to disseminate scientific knowledge, reaching other researchers, stakehold
 ers, and the broader public more effectively. The use of advanced visualiz
 ation tools (such as VTK and Paraview, ViSIT, or Blender) and render engin
 es (such as NVIDIA’s Barney and Blender Cycles), and the application of in
 formation visualization techniques can improve the quality of scientific v
 isualizations. This minisymposium addresses this topic by presenting diffe
 rent visualization workflows aimed towards the production of impactful vis
 uals from scientific data, in particular HPC simulation data. The four ses
 sions span a wide range of scientific applications in order to show how co
 mmon workflows might work independently of specific domains, and can addre
 ss general visualization challenges applicable across domains: Cosmologica
 l simulations, CFD, geophysics, and the visualization of ML-based analysis
 .\n\nMulti-Resolution Reconstruction of Large-Scale Scientific Data for Hi
 gh-Quality Visualization\n\nThe growing volume of data produced by scienti
 fic simulations in the exascale era poses\nmajor challenges for effective 
 visualization and analysis. We will present a method for\nreducing the siz
 e of large-scale simulation datasets by reconstructing them into\nmulti-re
 solution grids, enabling the genera...\n\n\nMarkéta Faltýnková (IT4Innovat
 ions, VŠB - Technical University of Ostrava)\n---------------------\nVisua
 lization of the 11 November 2019 Le Teil Earthquake: Towards a Digital Twi
 n on the Seismic Hazard?\n\nThe earthquakes in the intraplate domain (e.g.
  in European France) are either unexplained or can occur  in unexpected lo
 cations. Visualization can be highly effective in anticipating the seismic
  risk and driving stakeholder action. This session will focus on advanced 
 visualizations for geohazards, p...\n\n\nAndré Burnol (BRGM - French Geolo
 gical Survey) and Philippe P. Pébaÿ (NexGen Analytics)\n------------------
 ---\nFrom Visualization to Knowledge Discovery\n\nMachine learning–assiste
 d analysis is now widespread in Astrophysics, but its scope is still narro
 w, mostly focusing on regression, classification, and anomaly detection ta
 sks. On the other hand, the development of general visualization, explorat
 ion, and discovery tools has lagged behind. This...\n\n\nSebastian Trujill
 o-Gomez and Bernd Doser (Heidelberg Institute for Theoretical Studies)\n--
 -------------------\nCinematic Visualization of Large Simulation Datasets\
 n\nScientific visualization software often lacks advanced rendering engine
 s for photorealistic results, and fine control over the final quality of t
 he image. In contrast, cinematic software provides extensive control over 
 every aspect of image creation, as well as physically based rendering (PBR
 ) capab...\n\n\nGuillermo Marin (Barcelona Supercomputing Center, Universi
 tat Autònoma de Barcelona) and Miguel Esteban (Barcelona Supercomputing Ce
 nter)\n\nDomain: Applied Social Sciences and Humanities, Computational Met
 hods and Applied Mathematics\n\nSession Chairs: Guillaume Houzeaux (Barcel
 ona Supercomputing Center) and Guillermo Marin (Barcelona Supercomputing C
 enter, Universitat Autònoma de Barcelona)
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