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Communications of the ACM

ACM TechNews

Visualizing Scientific Big Data in Informative and Interactive Ways

Brookhaven National Laboratory

Wei Xu, a computer scientist who is part of Brookhaven National Laboratory's Computational Science Initiative.

Wei Xu, a computer scientist who is part of Brookhaven Labs Computational Science Initiative, helps scientists analyze large and varied datasets by developing visualization tools

Credit: Brookhaven National Laboratory

Wei Xu at the U.S. Department of Energy's Brookhaven National Laboratory is leading the development of visualization tools for analyzing large and varied datasets.

"We are dealing with an unsolved problem: how can we most efficiently and effectively understand the data?" Xu says.

In collaboration with Stony Brook University, Xu helped create an automated technique for mapping data with multiple variables to color, which she says would be useful for any multi-variable image dataset.

Xu's team also is developing an interactive multilevel display for large image-set exploration, enabling researchers to see all levels in a single view so identifying relationships between the raw data and analyzing data across the entire sample is possible.

A third tool developed with Xu's help can enable users to reconstruct all possible solutions to a given problem and pinpoint the subset of preferred solutions via interactive filtering.

From Brookhaven National Laboratory
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