WAVE: A 3D Online Previewing Framework for Big Data Archives

Nicholas Tan Jerome, Suren Chilingaryan, Andrei Shkarin, Andreas Kopmann, Michael Zapf, Alexander Lizin, Till Bergmann

Abstract

With data sets growing beyond terabytes or even petabytes in scientific experiments, there is a trend of keeping data at storage facilities and providing remote cloud-based services for analysis. However, accessing these data sets remotely is cumbersome due to additional network latency and incomplete metadata description. To ease data browsing on remote data archives, our WAVE framework applies an intelligent cache management to provide scientists with a visual feedback on the large data set interactively. In this paper, we present methods to reduce the data set size while preserving visual quality. Our framework supports volume rendering and surface rendering for data inspection and analysis. Furthermore, we enable a zoom-on-demand approach, where a selected volumetric region is reloaded with higher details. Finally, we evaluated theWAVE framework using a data set from the entomology science research.

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Paper Citation


in Harvard Style

Tan Jerome N., Chilingaryan S., Shkarin A., Kopmann A., Zapf M., Lizin A. and Bergmann T. (2017). WAVE: A 3D Online Previewing Framework for Big Data Archives . In Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: IVAPP, (VISIGRAPP 2017) ISBN 978-989-758-228-8, pages 152-163. DOI: 10.5220/0006228101520163


in Bibtex Style

@conference{ivapp17,
author={Nicholas Tan Jerome and Suren Chilingaryan and Andrei Shkarin and Andreas Kopmann and Michael Zapf and Alexander Lizin and Till Bergmann},
title={WAVE: A 3D Online Previewing Framework for Big Data Archives},
booktitle={Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: IVAPP, (VISIGRAPP 2017)},
year={2017},
pages={152-163},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006228101520163},
isbn={978-989-758-228-8},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: IVAPP, (VISIGRAPP 2017)
TI - WAVE: A 3D Online Previewing Framework for Big Data Archives
SN - 978-989-758-228-8
AU - Tan Jerome N.
AU - Chilingaryan S.
AU - Shkarin A.
AU - Kopmann A.
AU - Zapf M.
AU - Lizin A.
AU - Bergmann T.
PY - 2017
SP - 152
EP - 163
DO - 10.5220/0006228101520163