SeisFinder is an open-source web service developed by QuakeCoRE and the University of Canterbury, focused on enabling the extraction of output data from computationally intensive earthquake resilience calculations. Currently, SeisFinder allows users to select historical or future events and retrieve ground motion simulation outputs for requested geographical locations. This data can be used as input for other resilience calculations, such as dynamic response history analysis. SeisFinder was developed using Django, a high-level python web framework, and uses a postgreSQL database. Because our large-scale computationally-intensive numerical ground motion simulations produce big data, the actual data is stored in file systems, while the metadata is stored in the database.
Overview of SeisFinder SeisFinder is an open-source web service developed by QuakeCoRE and the University of Canterbury, focused on enabling the extraction of output data from computationally intensive earthquake resilience calculations. Currently, SeisFinder allows users to select historical or future events and retrieve ground motion simulation outputs for requested geographical locations. This data can be used as input for other resilience calculations, such as dynamic response history analysis. SeisFinder was developed using Django, a high-level python web framework, and uses a postgreSQL database. Because our large-scale computationally-intensive numerical ground motion simulations produce big data, the actual data is stored in file systems, while the metadata is stored in the database. The basic SeisFinder architecture is shown in Figure 1.
The M7.8 Kaikoura Earthquake in 2016 presented a number of challenges to science agencies and institutions throughout New Zealand. The earthquake was complex, with 21 faults rupturing throughout the North Canterbury and Marlborough landscape, generating a localised seven metre tsunami and triggering thousands of landslides. With many areas isolated as a result, it presented science teams with logistical challenges as well as the need to coordinate efforts across institutional and disciplinary boundaries. Many research disciplines, from engineering and geophysics to social science, were heavily involved in the response. Coordinating these disciplines and institutions required significant effort to assist New Zealand during its most complex earthquake yet recorded. This paper explores that effort and acknowledges the successes and lessons learned by the teams involved.
