Demo – Paper 558

Big Data Processing and Semantic Web Technologies for Decision Making in Hazardous Substance Dispersion Emergencies

Athanasios Davvetas, Iraklis Klampanos, Spyros Andronopoulos, Giannis Mouchakis, Stasinos Konstantopoulos, Andreas Ikonomopoulos and Vangelis Karkaletsis

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Abstract

Emergencies that involve the release of hazardous substances into the atmosphere affects life and nature for several years. The timely and reliable estimation of the expected consequences on people and the environment facilitates informed decision making and timely response. Here, we demonstrate a tool that leverages Big Data and Semantic Web technologies to estimate the source location and the expected dispersion of the plume and to link this against geo-located data about people, infrastructure, industry and other production units, and any other information relevant to potential effects on the population and the environment.