- Nuclear & Particle Physics
- Isotope Research & Production
- RIKEN BNL Research Center
Computation and Data-Driven Discovery (C3D) Projects
Visual Analytics for Scientific Data Analysis and Exploration
This work aims to establish a prototype system that visually represents, explores, and interacts with extreme-scale multivariate scientific data to empower future science research at the National Synchrotron Light Source II (NSLS-II) and Center for Functional Nanomaterials (CFN). To our knowledge, there are no existing visualization and visual analytics solutions satisfying the unique requirements of NSLS-II, i.e., a visual analytic environment for extreme-scale data and complex analyses allowing scientists to better integrate, understand, and interact with their data and analysis.
An online visual analysis tool that can process, manipulate, and visualize extreme-scale data is critical for scientists to make the right decisions onsite and adjust their measurement strategies during an experiment. Therefore, we have identified two pilot projects that, according to scientific collaborators, have extreme difficulties with regard to two (2D)-, three (3D)- and high-dimensional data visualization; lack the capabilities for interactive strategic exploration of raw data, metadata, and analyzed results; and consequently impede gleaning the desired scientific insight.
ColormapND: Data-driven Color Mapping for Scientific Images Integration
We are developing a colorization tool that automatically assigns colors to data points where similar chemical ratios get related colors. Users can interactively correspond the values of the same data point in separate variables, manipulate how data points are distributed in the color space by altering color assignments based on domain knowledge, and enhance the contrast to show more details to differentiate even subtle ratio changes. This tool provides scientists with a convenient way to integrate multivariate 2D/3D sample data into one pseudo-color display, where they can analyze the sample component in an interactive way. This is extremely useful with high-dimensional data.
MultiSciView: Multivariate X-ray Scattering Image Exploration
MultiSciView, a multivariate scientific x-ray image visualization and exploration system for beamline-generated x-ray scattering data, is composed of three complementary and coordinated interactive visualizations to enable coordinated exploration across the images and their associated attribute and feature spaces. The first visualization features a multi-level, dedicated scatter plot visualization for image exploration at attribute, image, and pixel scales. The second visualization is a histogram-based attribute cross filter, where users can extract desired subset patterns from the data. The third is an attribute projection visualization designed for capturing material global attribute correlations.