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Provenance-Aware Scalable Seismic Data Processing with Portability

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poster
posted on 31.01.2020 by Ian Wang

Most of our understanding about the Earth’s interior comes from seismology. Over the past decade, the huge success in many large-scale projects like the USArray component of Earthscope gave rise to a massive increase in the data volume available to the seismology community. Such data set has revealed the limitation of existing data processing infrastructure available to the seismologists. As a step towards addressing the issue, we devised a new framework we call Massive Parallel Analysis System for Seismologists (MsPASS), for seismic data processing and management. MsPASS leverages existing big data technologies: (1) a scalable parallel processing framework based on a dataflow computation model (Spark), (2) a NoSQL database system centered on document store (MongoDB), and (3) a container-based virtualization environment (Docker and Singularity).

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Elements: PASSPP: Provenance-Aware Scalable Seismic Data Processing with Portability

Directorate for Computer & Information Science & Engineering

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