LFPeers: Temporal Similarity Search in Covid-19 Data

Abstract

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.