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All Times EDT

Friday, October 2
Fri, Oct 2, 1:00 PM - 3:00 PM
Virtual
Poster Session 4

Improving Multi-Modal Analytics: Building Interfaces Using R (308543)

Emily Casleton , Los Alamos National Laboratory 
*Jenna Korobova, Los Alamos National Laboratory 
Tanvi Mehta, Los Alamos National Laboratory 

Keywords: R, R programming, LANL, data fusion, data visualization, data query, MongoDB, user interaction, nuclear non-proliferation

The overall goal of this project is to develop effective analytical methods that fuse data from multiple modalities to describe the patterns of life at a nuclear facility. Data is collected from many disparate modalities, including seismic, acoustic, radiation and EM, making it difficult to utilize. To increase utilization, we created functionality in R to use metadata to directly query data records stored in Echo, an internally developed data management tool. We also developed R functionality to filter data from these Echo records, generate plots, and create a Cinema viewer, an interactive image-based tool that allows the user to easily visualize desired subsets. Together, these R interfaces will allow for improved analysis of the targeted non-proliferation data.