Ontology based data warehouse modeling and mining of earthquake data: prediction analysis along Eurasian-Australian continental plates

Seismological observatories archive volumes of heterogeneous types of earthquake data. These organizations, by virtue of their geographic operations, handle complicated hierarchical data structures. In order to effectively and efficiently perform seismological observatories business activities, the flow of data and information must be consistent and information is shared among its units, situated at different geographic locations. In order to improve information sharing among observatories, heterogeneous nature of earthquake data from various sources are intelligently integrated. Data warehouse is a solution, in which, earthquake data entities are modeled using ontology-base multidimensional representation. These data are structured and stored in multi-dimensions in a warehousing environment to minimize the complexity of heterogeneous data. Authors are of the view that data integration process adds value to knowledge building and information sharing among different observatories. Authors suggest that warehoused data modeling facilitates earthquake prediction analysis more effectively.