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Web-based visual data exploration for improved radiological source detection

Journal Article · · Concurrency and Computation. Practice and Experience
DOI:https://doi.org/10.1002/cpe.4203· OSTI ID:1461119
 [1];  [2];  [2];  [2];  [2];  [2];  [2];  [2];  [2];  [2];  [2];  [2];  [2]
  1. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Univ. of California, Davis, CA (United States)
  2. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
+ Show Author Affiliations
Radiation detection can provide a reliable means of detecting radiological material. Such capabilities can help to prevent nuclear and/or radiological attacks, but reliable detection in uncontrolled surroundings requires algorithms that account for environmental background radiation. The Berkeley Data Cloud (BDC) facilitates the development of such methods by providing a framework to capture, store, analyze, and share data sets. In the era of big data, both the size and variety of data make it difficult to explore and find data sets of interest and manage the data. Thus, in the context of big data, visualization is critical for checking data consistency and validity, identifying gaps in data coverage, searching for data relevant to an analyst's use cases, and choosing input parameters for analysis. Downloading the data and exploring it on an analyst's desktop using traditional tools are no longer feasible due to the size of the data. This study describes the design and implementation of a visualization system that addresses the problems associated with data exploration within the context of the BDC. Finally, the visualization system is based on a JavaScript front end communicating via REST with a back end web server.
Research Organization:
Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
Sponsoring Organization:
Dept. of Homeland Security (DHS) (United States); USDOE National Nuclear Security Administration (NNSA), Office of Defense Nuclear Nonproliferation (NA-20)
Grant/Contract Number:
AC02-05CH11231
OSTI ID:
1461119
Journal Information:
Concurrency and Computation. Practice and Experience, Journal Name: Concurrency and Computation. Practice and Experience Journal Issue: 18 Vol. 29; ISSN 1532-0626
Publisher:
WileyCopyright Statement
Country of Publication:
United States
Language:
English

References (7)

FastQuery: A General Indexing and Querying System for Scientific Data book January 2011
RadMAP: The Radiological Multi-sensor Analysis Platform
  • Bandstra, Mark S.; Aucott, Timothy J.; Brubaker, Erik
  • Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, Vol. 840 https://doi.org/10.1016/j.nima.2016.09.040
journal December 2016
Brushing Scatterplots journal May 1987
The Human Genome Browser at UCSC journal May 2002
Visualization for situational awareness journal January 2000
D³ Data-Driven Documents journal December 2011
Rapid response radiation sensors for homeland security applications conference September 2014

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Related Subjects

96 KNOWLEDGE MANAGEMENT AND PRESERVATION
data integration
data storage and indexing
databases
visualization
web-based system