VERCE is a data-intensive e-science environment to enable innovative data analysis and data modelling methods that fully exploit the increasing wealth of open data generated by the observational and monitoring systems of the global seismology community.
The earthquake and seismology research, an intrinsically Global undertaking, addresses both fundamental problems in understanding Earth's internal wave sources and structures, and augment applications to societal concerns about natural hazards, energy resources, environmental change, and national security.
This community is central in the European Plate Observing System , the ESFRI initiative in solid Earth Sciences.
Global and regional seismology monitoring systems are continuously operated and transmitting a growing wealth of data from around the world. The multi-use nature of these data puts a great premium on open-access data infrastructures integrated globally. Most of the effort is in Europe, USA and Japan.
The European Integrated Data Archives infrastructure provides strong horizontal data services. Enabling advanced analysis of these data by utilising a data-aware distributed computing environment is instrumental to exploit fully the cornucopia of data, and to guarantee optimal operation and design of the high-cost monitoring facilities. The strategy of VERCE, driven by the needs of data-intensive applications in data mining and modelling, aims to provide a comprehensive architecture and framework adapted to the scale and the diversity of these applications, and integrating the community Data infrastructure with Grid and HPC infrastructures.
A first novel aspect of VERCE consists of integrating a service-oriented architecture with an efficient communication layer between the Data and the Grid infrastructures, and HPC. A second novel aspect is the coupling between HTC data analysis and HPC data modelling applications through workflow and data sharing mechanisms. VERCE will strengthen the European earthquake and seismology research competitiveness, and enhance the data exploitation and the modelling capabilities of this community. In turn, it will contribute to the European and National e-infrastructures.
