Scope

What a MESS! ObsPy meets archiving and simulation

• How can we efficiently get seismic event data (large data sets) from distributed data centres?

• How can we store seismological data and other information efficiently in a data base structure, so that the information can be shared and is sustainable (e.g., beyond project duration)

• How can simulated data be formally integrated in seismological research projects?

• How can we efficiently visualize geographical information related to seismological event information and actual waveforms

• How can we efficiently automate processing and storage of very large real and synthetic seismological data sets?

Scope:

In 2013 we will continue to offer training on the ObsPy python library (www.obspy.org) giving a general introduction, discussing new features such as ObsPyDMT and others. A common problem in seismology is an efficient archiving of seismic event data or other information in a relational data base. We will offer an introduction to the SeisHub data base (www.seishub.org). More technically, SeisHub is a novel web-based database approach created for archiving, processing, and sharing geophysical data and meta data, particularly adapted for seismology. Today, many projects in seismology involve the calculation of synthetic seismograms. Ideally, one should store and format these data in the same way as observations, to allow full integration in the data analysis and interpretation work flows. MESS 2013 will walk through such a complete cycle with processing and storage tools based on the python language. This will be complemented by training on the use of a 3-D spectral element solver (ses3d) for the generation of synthetic seismograms.

MESS  2013 addresses researchers who deal with large seismological or seismic data sets on all scales and seek new ways of solving the data deluge problem. Basic knowledge about the python language and packages helps. Bring your own data! We invite participant to bring their own data and use the processing and archiving tools on these data during the practicals (and beyond).