EpiViewer: An Epidemiological Application For Exploring Time Series Data

dc.contributor.authorThorve, Swapnaen
dc.contributor.committeechairMarathe, Madhav Vishnuen
dc.contributor.committeememberVullikanti, Anil Kumaren
dc.contributor.committeememberMarathe, Achlaen
dc.contributor.departmentComputer Scienceen
dc.date.accessioned2019-01-22T17:48:18Zen
dc.date.available2019-01-22T17:48:18Zen
dc.date.issued2018-11en
dc.description.abstractVisualization 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. However,there are challenges in reviewing data sets from multiple data sources (data can be aggregated in different ways and measure different criteria 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. In this thesis, we develop 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 a built-in statistical Epi-features module to help users interpret the epidemiological curves.en
dc.description.abstractgeneralWe 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 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.en
dc.description.degreeMaster of Scienceen
dc.format.mediumETDen
dc.identifier.urihttp://hdl.handle.net/10919/86829en
dc.language.isoen_USen
dc.publisherVirginia Techen
dc.rightsCreative Commons Attribution-NoDerivatives 3.0 United Statesen
dc.rights.urihttp://creativecommons.org/licenses/by-nd/3.0/us/en
dc.subjectweb servicesen
dc.subjectmodel view controller architectureen
dc.subjectcataloguesen
dc.subjectepidemiologyen
dc.subjectmetricsen
dc.subjectchartsen
dc.titleEpiViewer: An Epidemiological Application For Exploring Time Series Dataen
dc.typeThesisen
thesis.degree.disciplineComputer Science and Applicationsen
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen
thesis.degree.levelmastersen
thesis.degree.nameMaster of Scienceen

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