1. www.see-grid-sci.eu SEE-GRID-SCI SEE-GRID-SCI Seismology VO The SEE-GRID-SCI initiative is co-funded by the European Commission under the FP7 Research Infrastructures contract no. 211338 Can Özturan Seismic VO Leader

2. EGEE08, Istanbul, Sept 22-26, 2008 2/x Background/Overview Objectives:  Gridify some applications  Serve seismic data that is mirrored from national seismology centres using a high level interface that is easy to use/adapt.  Seek collaboration with other seismology related groups/organizations There exists other organizations/projects (e.g.) :  ORFEUS, NERIES In SEEGRID-SCI, we should avoid avoid duplicate work and contribute complementary work  Differentiate ourself by :  The grid platform  Performance aspects – (high performance computing, high performance access to massive data)

3. EGEE08, Istanbul, Sept 22-26, 2008 3/x Background/Overview  High level interface to data: avoid requiring the users of seismic data to:  learn a lot of new tools  write data location dependent code  modify existing applications drastically NERIES (closely related project):  Based on Web platform (provide data though portal and web services)  More comprehensive/larger scope

4. EGEE08, Istanbul, Sept 22-26, 2008 4/x Collaborating Organizations OrganizationCountry Polytechnic University of TiranaAlbania National Academy of Sciences of ArmeniaArmenia Seismological Department, in Geophysical Institute of BASBulgaria Department of Geophysics in Institute of Geography and Earth Sciences of Eötvös Loránd University Hungary Seismological Observatory of Geodetic and Geophysical Research Institute of Hungarian Academy of Sciences Hungary Faculty of Natural Sciences and Mathematics of University of Ss. Cyril and Methodius FYR of Macedonia Institute of Geology and Seismology of ASMMoldova Seismological Survey of SerbiaSerbia Kandilli Observatory and Earthquake Research Institute / Dept. of Computer Engineering, Boğaziçi University Turkey Middle East Technical University Turkey Earthquake Research Dept. of General Directorate of Disaster Affairs Turkey

5. EGEE08, Istanbul, Sept 22-26, 2008 5/x Seismology VO Platform In Seismology VO, as data, (i) official lists of earthquakes and stations, and (ii) massive seismic waveform data from various South Eastern European countries are planned to be collected and served. To realise the aims of the Seismology VO, the following are carried out: 1. Distributed storage of seismic data from different partner countries, 2. Logical organization, indexing and update of distributed seismic data, 3. Programming tools that will provide easy access to seismic data, 4. Gridification of various seismology applications: SRA, NMMC3D, FPS, ELF, MDSSP-WA, and SDS Time Station1 Station 2 Station 3 Station 4 2002 2003 2004 2005 Form of data:

6. EGEE08, Istanbul, Sept 22-26, 2008 6/x Seismology VO Platform Applications Programming Tools (C++Iterators) Earthquake and seismic waveform data (country 2) Distributed storage and indexing of data on grid (using distributed storage elements, LFC and AMGA) Earthquake and seismic waveform data (country n) Earthquake and seismic waveform data (country 1)

7. EGEE08, Istanbul, Sept 22-26, 2008 7/x Applications ApplicationMain DeveloperCollaborators Seismic Risk Assessment (SRA)Middle East Technical University (TR)Institute of Geology and Seismology of ASM (MD), Boğaziçi University (TR) Numerical Modelling of Mantle Convection in 3D (NMMC3D) Seismological Observatory of Geodetic and Geophysical Research Institute of Hungarian Academy of Sciences (HU) Department of Geophysics in Institute of Geography and Earth Sciences of Eötvös Loránd University (HU) Fault Plane Solution (FPS)Boğaziçi University (TR) Massive Digital Seismological Signal Processing with the Wavelet Analysis (MDSSP- WA) Faculty of Natural Sciences and Mathematics of University of Ss. Cyril and Methodius (MK) Seismological Department, in Geophysical Institute of BAS (BG), Seismological Survey of Serbia (RS), Boğaziçi University (TR) Earthquake Location Finding (ELF)Boğaziçi University (TR)University of Ss Cyril and Methodius (MK), Middle East Technical University (TR) Seismic Data Server (application service and web interface) (SDS) Boğaziçi University (TR)Polytechnic University of Tirana (AL), National Academy of Sciences of Armenia (AM), Institute of Geology and Seismology of ASM (MD), Ss Cyril and Methodius University of Skopje (MK), Earthquake Research Dept. of General Directorate of Disaster Affairs (TR), Middle East Technical University (TR)

8. EGEE08, Istanbul, Sept 22-26, 2008 8/x SEISMIC RISK ASSESMENT (SRA) Seismic Risk Assessment is very important for public safety and hazards mitigation. It is also important for the correct determination of earthquake insurance premiums and also for understanding the social and psychological effects of earthquakes. Our aim is to develop an application framework to allow us to embed alternative (deterministic, probabilistic etc.) models. SRA application can be grouped into four main categories: (i) Accessing Earthquake Catalogue, (ii) Earthquake Source Model (iii) Seismic Hazard Models (iv) Producing Seismic Hazard Maps

9. EGEE08, Istanbul, Sept 22-26, 2008 9/x NUMERICAL MODELING OF MANTLE CONVECTION – NMMC3D The outer part of the Earth consist of moving, rotating and interacting plates. The motion of these plates suggest a large convective system in the Earth's 2900 thick layer, the mantle. The numerical calculations suggested that the convective cells are formed by sheet-like elongated downwellings (subduction zones) and narrow, cylindrical upwellings (mantle plumes, at the hotspots). The main goal of our research is the quantitative study of the structure and surface manifestation of mantle plumes and to make systematic investigation of the parameters influencing the character of mantle convection in 3D.

10. EGEE08, Istanbul, Sept 22-26, 2008 10/x Fault Plane Solution (FPS) Computes earthquake source parameters (strike, slip, dip) Inputs:  Crust model: layer thicknesses, seismic velocities, densities, q-factor  Actual seismic waveform data (in SAC format) Output:  Fault paramtheters Useful for identifying tectonic structures that are not visible on earth’s surface Computationally intensive application A typical run that uses data from 50 stations takes 8 hours on a PC Implemented in Fortran/C

11. EGEE08, Istanbul, Sept 22-26, 2008 11/x Massive Digital Seismological Signal Processing with the Wavelet Analysis(MDSSP-WA) Wavelet theory has matured in past years as new mathematical tool for time series analysis. The continuous or discrete wavelet transforms and relevant plotting of the results in coordinate system, scales versus time, shows striking similarity of the wavelet images, between different seismic records, coming from the same source region or noticeable difference for records of earthquakes occurred in different source region. We assume that, those similar image patterns are due to same underlying geological setting while the differences (usually for smaller scale) is due to different source mechanism and finer geological structures. In the first approximation of geological structure, similarities of the image patterns in domain of large scale are noticeable even for the records from different source regions. With massive processing of earthquake records we can define: (i) Common features of the propagation path for the given seismic source region or to define empirical transfer function of the media (ii) Calculation of the artificial seismograms, (iii) Determine the source region based on a single earthquakes record (iv) Determine the more realistic attenuation curve of the selected feature (parameter), very much needed in seismic hazard and risk analysis, (v) Mapping (coding) of the given earthquake prone region in terms of selected parameters (vi)Seismic source parameters

12. EGEE08, Istanbul, Sept 22-26, 2008 12/x Earthquake Location Finding (ELF) This application is based on HYPO71 and finds the location of earthquakes by scanning seismic waveform data. This application is not compute intensive, but it is data intensive. The application can be parallelized by scanning data files in parallel by multiple using worker nodes. A workflow can be generated automatically by a program corresponding to the time intervals in which to look for earthquake

13. EGEE08, Istanbul, Sept 22-26, 2008 13/x Seismic Data Server (SDS) Application Service SDSAS is a JRA1 service that serves massive seismic data that are archived from national seismology centers using a high level interface that is easy to use/adapt. It serves official lists of earthquakes, stations, sensor information. It keeps the details of where the data files reside are hidden by mapping high level user specifications (dates, hours, location etc.) to appropriate pathnames. The SDSAS implementation will be done by using scripts to collect and organizing the seismic data by utilizing storage elements, LFC and AMGA. C++ iterators can be used by applications to access station data, earthquake data and information about seismic waveform files.

14. EGEE08, Istanbul, Sept 22-26, 2008 14/x Seismic Data Server (SDS) Application Service #include "sds.h" #include using namespace sds ; main() { SDS_Init sdsinit ; SDS_Date_Range dr( SDS_Date(2003,Jan,10), SDS_Date(2003,Feb,11) ) ; SDS_Quakes q(SDS_All,dr) ; SDS_Quakes_Iterator qend = q.end() ; for (SDS_Quakes_Iterator i = q.begin(); i != qend ; i++) { cout << (*i).latitude << endl; } q.kml("kmlfile") ; } Example

15. EGEE08, Istanbul, Sept 22-26, 2008 15/x SDS Web Interface Serving of seismic data present in AMGA tables (station data, earthquake data and information about seismic waveform files - not waveform files themselves) through a web interface that utilizes kml and Google Earth api.