Large data usage in seismology: use cases and workflows
We request feedback from researchers processing, or plans to process, large data volumes (~1 terabyte or greater).

While the volume of traditional broadband and short period data continues to increase, new technologies such as Distributed Acoustic Sensing (DAS) and nodal systems are driving a step function in data volumes at data centers.  The increase in data volumes and types, paired with increasing availability of compute resources, will require new data access and processing capabilities.

As seismological data centers adapt their infrastructures and services to more and different data, we will use this feedback to guide our developments.

- GEOFON (Germany), RESIF (France), IRIS DMC (USA)


İlerleme durumunu kaydetmek için Google'da oturum açın Daha fazla bilgi
What is the maximum size of the datasets you anticipate working with in the next 3-5 years?
What data type are the raw data (e.g. broadband, nodal, DAS)?
From which data centers do you expect to request large data volumes?
In which data format(s) would you prefer to work with large data (miniSEED, SAC, PH5, ASDF, HDF5, etc.)?
Which software would you use to access/download large data volumes (libraries, applications, etc.)?
Would you process the data with standard codes?  With your own code?  Using third party frameworks and libraries (e.g. ObsPy)?
Which programming language(s) do you, or would you expect to, use for data processing and analysis?
Where would you prefer the data to be delivered: your own compute infrastructure, a cloud system, an HPC center?
Would you be willing to pay for the data processing resources (e.g. compute) if the data are available within a commercial cloud or other environment that is not free to use?
Please briefly summarize your current large data processing workflow, trouble points identified/foreseen, and how it can be improved.
Other comments or wishes for your vision of the processing of large seismic data in the future?
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