Data reduction is increasingly being applied to scientific data for numerical simulations, scientific visualizations, and data analyses. It is most often used to lower I/O and storage costs, and sometimes to lower in-memory data size as well. With this work, we consider five categories of data reduction techniques based on their information loss: 1) truly lossless, 2) near lossless, 3) lossy, 4) mesh reduction, and 5) derived representations. We then survey available techniques in each of these categories, summarize their properties from a practical point of view, and discuss relative merits within a category. We believe, in total, this work will enable simulation scientists and visualization/data analysis scientists to decide which data reduction techniques will be most helpful for their needs.
Li, Shaomeng, et al. "Data Reduction Techniques for Simulation, Visualization and Data Analysis." Computer Graphics Forum, vol. 37, no. 6, Mar. 2018. https://doi.org/10.1111/cgf.13336
Li, Shaomeng, Marsaglia, Nicole, Garth, Christoph, et al., "Data Reduction Techniques for Simulation, Visualization and Data Analysis," Computer Graphics Forum 37, no. 6 (2018), https://doi.org/10.1111/cgf.13336
@article{osti_1463451,
author = {Li, Shaomeng and Marsaglia, Nicole and Garth, Christoph and Woodring, Jonathan and Clyne, John and Childs, Hank},
title = {Data Reduction Techniques for Simulation, Visualization and Data Analysis},
annote = {Data reduction is increasingly being applied to scientific data for numerical simulations, scientific visualizations, and data analyses. It is most often used to lower I/O and storage costs, and sometimes to lower in-memory data size as well. With this work, we consider five categories of data reduction techniques based on their information loss: 1) truly lossless, 2) near lossless, 3) lossy, 4) mesh reduction, and 5) derived representations. We then survey available techniques in each of these categories, summarize their properties from a practical point of view, and discuss relative merits within a category. We believe, in total, this work will enable simulation scientists and visualization/data analysis scientists to decide which data reduction techniques will be most helpful for their needs.},
doi = {10.1111/cgf.13336},
url = {https://www.osti.gov/biblio/1463451},
journal = {Computer Graphics Forum},
issn = {ISSN 0167-7055},
number = {6},
volume = {37},
place = {United States},
publisher = {Wiley},
year = {2018},
month = {03}}
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