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LFPeers: Temporal Similarity Search in Covid-19 Data

: Burmeister, Jan; Bernard, Jürgen; Kohlhammer, Jörn


Bernard, Jürgen (Ed.) ; European Association for Computer Graphics -EUROGRAPHICS-:
EuroVA 2021, EuroVis Workshop on Visual Analytics : June 14, 2021
Goslar: Eurographics Association, 2021
ISBN: 978-3-03868-150-2
5 S.
International Workshop on Visual Analytics (EuroVA) <12, 2021, Online>
Fraunhofer IGD ()
Lead Topic: Individual Health; Research Line: Modeling (MOD); corona; Visual analytics; similarity search; time series data visualization

While there is a wide variety of visualizations and dashboards to help understand the data of the Covid-19 pandemic, hardly any of these support important analytical tasks, especially of temporal attributes. In this paper, we introduce a general concept for the analysis of temporal and multimodal data and the system LFPeers that applies this concept to the analysis of countries in a Covid-19 dataset. Our concept divides the analysis in two phases: a search phase to find the most similar objects to a target object before a time point t0, and an exploration phase to analyze this subset of objects after t0. LFPeers targets epidemiologists and the public who want to learn from the Covid-19 pandemic and distinguish successful and ineffective measures.