Rydow E, Gönen T, Kachkaev A, Khan S. RAMPVIS: A visualization and visual analytics infrastructure for COVID-19 data.
SOFTWAREX 2023:101416. [PMID:
37361907 PMCID:
PMC10203881 DOI:
10.1016/j.softx.2023.101416]
[Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/25/2023] [Revised: 05/09/2023] [Accepted: 05/17/2023] [Indexed: 06/28/2023]
Abstract
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.
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