Abstract:

National Data Centres (NDCs) responsible for nuclear weapon test verification face a critical analytical challenge: systematically identifying radionuclide samples that may share common source regions. Current tools from the Comprehensive Nuclear-Test-Ban Treaty Organization (CTBTO) fragment workflows across separate applications for spectrum analysis, timeseries visualization, and atmospheric transport modeling, forcing analysts to manually compare samples through ad hoc Excel-based methods. We present RaDIA (Radionuclide Data Integration and Analysis), a visual analytics dashboard that integrates sample metadata, isotopic measurements, and source-receptor sensitivity (SRS) fields into coordinated multiple views. RaDIA implements a spatial overlap detection algorithm that quantifies associations between samples by calculating shared grid cells in backward atmospheric trajectories, visualized through interactive maps, temporal Sankey diagrams, and sortable tables. Through Research-through-Design with three NDCs, we show that RaDIA addresses documented workflow gaps by consolidating fragmented tools, thereby alleviating user effort, and enabling systematic sample association. Our work suggests how domain-specific visual analytics can strengthen analytical capacity for smaller NDCs in high-stakes verification contexts.

Cite (BibTeX):

@inproceedings{verherstraeten2026radia,
  author    = {Verherstraeten, Stian and Gueibe, Christophe and Rovelo Ruiz, Gustavo and Luyten, Kris},
  title     = {RaDIA: Visual analytics for systematic sample association in nuclear weapon test verification workflows},
  booktitle = {Companion proceedings of the 18th ACM SIGCHI symposium on engineering interactive computing systems},
  series    = {EICS companion '26},
  year      = {2026},
  publisher = {ACM},
  address   = {New York, NY, USA},
  doi       = {10.1145/3807968.3810929}
}