Designing of Ontology for the Classification of Earthquakes

Abstract

Japan is an earthquake-prone country, with 1,000 to 2,000 sensible earthquakes observed per year. Seismological research is also active, and the Japan Meteorological Agency, the National Research Institute for Earth Science and Disaster Prevention, and local governments have established seismic observation networks. In recent years, various studies have been conducted to detect, classify, and predict the intensity of earthquakes using machine learning techniques based on the large amount of observed seismic waveform data. Therefore, it is necessary for researchers to set and collect the location of the hypocenter, time of occurrence, and target observation points in order to create data for training purposes. In this paper, we construct an earthquake ontology and assign URIs to earthquakes based on observed waveforms and hypocenters to investigate the availability and distribution of earthquake catalogs that can be used as learning data.