Treffer: An Adaptable Seismic Data Format

Title:
An Adaptable Seismic Data Format
Contributors:
Department of Earth and Environmental Sciences [München], Ludwig Maximilian University [Munich] = Ludwig Maximilians Universität München (LMU), Department of Geosciences [Princeton], Princeton University, University of Toronto - Department of physics, Oak Ridge National Laboratory [Oak Ridge] (ORNL), UT-Battelle, LLC, Géoazur (GEOAZUR 7329), Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire de la Côte d'Azur, Université Côte d'Azur (UniCA)-Université Côte d'Azur (UniCA)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [Occitanie])
Source:
Geophysical Journal International. 207(2):1003-1011
Publisher Information:
CCSD; Oxford University Press (OUP), 2016.
Publication Year:
2016
Collection:
collection:IRD
collection:INSU
collection:CNRS
collection:OCA
collection:GEOAZUR
collection:UNIV-COTEDAZUR
collection:UNIV-COTEDAZUR_COLLECTION_DEFAUT
collection:TEST-NICE
Original Identifier:
HAL: hal-01534788
Document Type:
Zeitschrift article<br />Journal articles
Language:
English
ISSN:
0956-540X
1365-246X
Relation:
info:eu-repo/semantics/altIdentifier/doi/10.1093/gji/ggw319
DOI:
10.1093/gji/ggw319
Rights:
info:eu-repo/semantics/OpenAccess
URL: http://creativecommons.org/licenses/by/
Accession Number:
edshal.hal.01534788v1
Database:
HAL

Weitere Informationen

We present ASDF, the Adaptable Seismic Data Format, a modern and practical data format for all branches of seismology and beyond. The growing volume of freely available data coupled with ever expanding computational power opens avenues to tackle larger and more complex problems. Current bottlenecks include inefficient resource usage and insufficient data organization. Properly scaling a problem requires the resolution of both these challenges, and existing data formats are no longer up to the task. ASDF stores any number of synthetic, processed or unaltered waveforms in a single file. A key improvement compared to existing formats is the inclusion of comprehensive meta information, such as event or station information, in the same file. Additionally, it is also usable for any non-waveform data, for example, cross-correlations, adjoint sources or receiver functions. Last but not least, full provenance information can be stored alongside each item of data, thereby enhancing reproducibility and accountability. Any data set in our proposed format is self-describing and can be readily exchanged with others, facilitating collaboration. The utilization of the HDF5 container format grants efficient and parallel I/O operations, integrated compression algorithms and check sums to guard against data corruption. To not reinvent the wheel and to build upon past developments, we use existing standards like QuakeML, StationXML, W3C PROV and HDF5 wherever feasible. Usability and tool support are crucial for any new format to gain acceptance. We developed mature C/Fortran and Python based APIs coupling ASDF to the widely used SPECFEM3D_GLOBE and ObsPy toolkits.