A Scalable System for Visual Analysis of Ocean Data.

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Bibliographic Details
Title: A Scalable System for Visual Analysis of Ocean Data.
Authors: Jain, Toshit1 (AUTHOR) f20170201h@alumni.bits-pilani.ac.in, Singh, Upkar1 (AUTHOR) upkarsingh@iisc.ac.in, Singh, Varun1 (AUTHOR) f20180869@goa.bits-pilani.ac.in, Boda, Vijay Kumar1 (AUTHOR) kbvijay@alum.iisc.ac.in, Hotz, Ingrid1,2 (AUTHOR) ingrid.hotz@liu.se, Vadhiyar, Sathish S.3 (AUTHOR) vss@iisc.ac.in, Vinayachandran, P. N.4 (AUTHOR) vinay@iisc.ac.in, Natarajan, Vijay1,5 (AUTHOR) vijayn@iisc.ac.in
Source: Computer Graphics Forum. Feb2025, Vol. 44 Issue 1, p1-19. 19p.
Subjects: Task analysis, Scientific visualization, Databases, Systems design, Oceanographers
Abstract: Oceanographers rely on visual analysis to interpret model simulations, identify events and phenomena, and track dynamic ocean processes. The ever increasing resolution and complexity of ocean data due to its dynamic nature and multivariate relationships demands a scalable and adaptable visualization tool for interactive exploration. We introduce pyParaOcean, a scalable and interactive visualization system designed specifically for ocean data analysis. pyParaOcean offers specialized modules for common oceanographic analysis tasks, including eddy identification and salinity movement tracking. These modules seamlessly integrate with ParaView as filters, ensuring a user‐friendly and easy‐to‐use system while leveraging the parallelization capabilities of ParaView and a plethora of inbuilt general‐purpose visualization functionalities. The creation of an auxiliary dataset stored as a Cinema database helps address I/O and network bandwidth bottlenecks while supporting the generation of quick overview visualizations. We present a case study on the Bay of Bengal to demonstrate the utility of the system and scaling studies to evaluate the efficiency of the system. [ABSTRACT FROM AUTHOR]
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Database: Engineering Source
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Abstract:Oceanographers rely on visual analysis to interpret model simulations, identify events and phenomena, and track dynamic ocean processes. The ever increasing resolution and complexity of ocean data due to its dynamic nature and multivariate relationships demands a scalable and adaptable visualization tool for interactive exploration. We introduce pyParaOcean, a scalable and interactive visualization system designed specifically for ocean data analysis. pyParaOcean offers specialized modules for common oceanographic analysis tasks, including eddy identification and salinity movement tracking. These modules seamlessly integrate with ParaView as filters, ensuring a user‐friendly and easy‐to‐use system while leveraging the parallelization capabilities of ParaView and a plethora of inbuilt general‐purpose visualization functionalities. The creation of an auxiliary dataset stored as a Cinema database helps address I/O and network bandwidth bottlenecks while supporting the generation of quick overview visualizations. We present a case study on the Bay of Bengal to demonstrate the utility of the system and scaling studies to evaluate the efficiency of the system. [ABSTRACT FROM AUTHOR]
ISSN:01677055
DOI:10.1111/cgf.15279