Data and Analytics, Technology and Market

Interactive Data Visualization for Public Health Applications: An Evaluation of Plotly’s Capabilities


Leveraging multiple data variables is critical for effective infectious disease outbreak management. Contextual actionable data provided to decision makers is often best analyzed and conveyed visually. However, limited human resources and collaborative platforms create many challenges for the effective use of data.  B.Next executed a project to explore, evaluate, and demonstrate how and to what extent information technology capabilities might empower public health analysts with limited or no coding experience to create enhanced data visualizations during an infectious disease outbreak. Dynamic visualizations with multiple variables have proven beneficial in past epidemic management operations for situational awareness. The popular tools available to produce interactive visualizations require financial resources beyond what is often available to state and local public health organizations or coding expertise to utilize open source coding libraries such as JavaScript, R, and Python. This report outlines the methods and results of a B.Next project with Plotly, a company that creates open source tools for visualization, to further develop their existing web-based interface to create interactive cross-filtering visualizations with multivariate datasets for non-coders.  Plotly enhanced their Chart Studio tool to enable cross-filtering functionalities with nine different charts in a dashboard display. An evaluation of Plotly’s enhancement was completed by both public health subject matter experts and IQT Labs personnel with expertise in infectious disease and visualization tools. The evaluation suggests that the cross-filtering functionality within Plotly provides new capabilities accessible to non-coders. However, Plotly needs additional improvements to compete with more intuitive interfaces such as Tableau.  

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