Web-based visual data exploration for improved radiologicalrnsource detection

摘要

Radiation detection can provide a reliable means of detecting radiologicalmaterial. Such capabilitiesrncan help to prevent nuclear and/or radiological attacks, but reliable detection in uncontrolledrnsurroundings requires algorithms that account for environmental background radiation. ThernBerkeley Data Cloud (BDC) facilitates the development of such methods by providing a frameworkrnto capture, store, analyze, and share data sets. In the era of big data, both the size and varietyrnof data make it difficult to explore and find data sets of interest andmanage the data. Thus, in therncontext of big data, visualization is critical for checking data consistency and validity, identifyingrngaps in data coverage, searching for data relevant to an analyst's use cases, and choosing inputrnparameters for analysis. Downloading the data and exploring it on an analyst's desktop using traditionalrntools are no longer feasible due to the size of the data. This paper describes the designrnand implementation of a visualization system that addresses the problems associated with datarnexplorationwithin the context of the BDC. The visualization system is based on a JavaScript frontrnend communicating via REST with a back end web server.