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

التفاصيل البيبلوغرافية
العنوان: RAMPVIS: A visualization and visual analytics infrastructure for COVID-19 data
المؤلفون: Rydow, Erik, Gönen, Tuna, Kachkaev, Alexander, Khan, Saiful
المصدر: SoftwareX; 20230101, Issue: Preprints
مستخلص: 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.
قاعدة البيانات: Supplemental Index
الوصف
تدمد:23527110
DOI:10.1016/j.softx.2023.101416