NBIC and DTRA, An Interagency Partnership to  Integrate Analyst Capabilities

Mui, Wai-Ling; Argenta, Edward P.; Quitugua, Teresa; Kiley, Christopher

doi:10.5210/ojphi.v9i1.7624

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“…An example of this is the integration of EpiViewer into the Biosurveillance Ecosystem (BSVE), a large-scale analytics platform funded by the Defense Threat Reduction Agency (DTRA) for the analysis, visualization, and curation of real-time global epidemic and outbreak data. BSVE has a repository of data sources collated by DTRA, Los Alamos National Laboratories, and others [ 12 , 13 ]. While BSVE offers applications customized to provide visualizations and analytical methods for specific data sources within its repository, EpiViewer allows users to compare data across multiple data sources along with their own data, which can lead to a more complete view on how an epidemic is progressing.…”

Section: Introductionmentioning

confidence: 99%

EpiViewer: an epidemiological application for exploring time series data

et al. 2018

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BackgroundVisualization plays an important role in epidemic time series analysis and forecasting. Viewing time series data plotted on a graph can help researchers identify anomalies and unexpected trends that could be overlooked if the data were reviewed in tabular form; these details can influence a researcher’s recommended course of action or choice of simulation models. However, there are challenges in reviewing data sets from multiple data sources – data can be aggregated in different ways (e.g., incidence vs. cumulative), measure different criteria (e.g., infection counts, hospitalizations, and deaths), or represent different geographical scales (e.g., nation, HHS Regions, or states), which can make a direct comparison between time series difficult. In the face of an emerging epidemic, the ability to visualize time series from various sources and organizations and to reconcile these datasets based on different criteria could be key in developing accurate forecasts and identifying effective interventions. Many tools have been developed for visualizing temporal data; however, none yet supports all the functionality needed for easy collaborative visualization and analysis of epidemic data.ResultsIn this paper, we present EpiViewer, a time series exploration dashboard where users can upload epidemiological time series data from a variety of sources and compare, organize, and track how data evolves as an epidemic progresses. EpiViewer provides an easy-to-use web interface for visualizing temporal datasets either as line charts or bar charts. The application provides enhanced features for visual analysis, such as hierarchical categorization, zooming, and filtering, to enable detailed inspection and comparison of multiple time series on a single canvas. Finally, EpiViewer provides several built-in statistical Epi-features to help users interpret the epidemiological curves.ConclusionEpiViewer is a single page web application that provides a framework for exploring, comparing, and organizing temporal datasets. It offers a variety of features for convenient filtering and analysis of epicurves based on meta-attribute tagging. EpiViewer also provides a platform for sharing data between groups for better comparison and analysis. Our user study demonstrated that EpiViewer is easy to use and fills a particular niche in the toolspace for visualization and exploration of epidemiological data.Electronic supplementary materialThe online version of this article (10.1186/s12859-018-2439-0) contains supplementary material, which is available to authorized users.

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Section: Introductionmentioning

confidence: 99%