RAMPVIS: A visualization and visual analytics infrastructure for COVID-19 data.

Publication date: May 23, 2023

The COVID-19 pandemic generated large amounts of diverse data, including testing, treatments, vaccine trials, data from modeling, etc. To support epidemiologists and modeling scientists in their efforts to understand and respond to the pandemic, there arose a need for web visualization and visual analytics (VIS) applications to provide insights and support decision-making. In this paper, we present RAMPVIS, an infrastructure designed to support a range of observational, analytical, model-developmental, and dissemination tasks. One of the main features of the system is the ability to “propagate” a visualization designed for one data source to similar ones, this allows a user to quickly visualize large amounts of data. In addition to the COVID pandemic, the RAMPVIS software may be adapted and used with different data to provide rapid visualization support for other emergency responses.

Concepts Keywords
Adapted COVID-19
Informatics Data visualization
Large Model development
Pandemic Ontology
Vaccine Pandemic responses
Visual analytics


Type Source Name
disease MESH COVID-19
disease VO vaccine
disease MESH emergency

Original Article

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