1. Seismo-Surfer a tool for collecting, querying, and mining seismic data Yannis Theodoridis University of Piraeus ytheod@unipi.gr

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3. 3 Outline of the presentation Concepts and motivation The Seismo-Surfer tool  Architecture  Functionality  Current status Future work Conclusions

4. 4 Concepts and motivation (1) Seismic data are recorded by seismologists (geologists etc.) in order to study tectonic activity. This kind of data is characterized by several attribute types  alphanumeric (e.g. magnitude)  spatial (epicenter, depth)  temporal (time of occurrence)

5. 5 Concepts and motivation (2) Goal: to build a prototype system (tool) of practical impact that combines results of latest research trends in the fields of  Non-traditional databases (spatio-temporal)  Data warehousing  Data mining by using state-of-the-art DBMS technology. … all this into a user-friendly environment.

6. 6 Concepts and motivation (3) Such a tool could be useful to  researchers of geophysical sciences (e.g. for constructing seismic profiles).  key personnel in public administration (e.g. for visualizing epicenters and relating them with other spatial entities).  simple users (e.g. web-surfers seeking for maps of seismic activity).  The Seismo-Surfer tool

7. 7 Seismo-Surfer Architecture

8. 8 Seismo-Surfer Functionality (1) Non-traditional queries (spatial and spatio-temporal)  “find all epicentres of earthquakes within distance no more than 50Km from Athens in the last 10 years” Data warehouse functionality by supporting summarized views of data in different levels of abstraction  spatial (e.g. province, country, continent)  temporal (e.g. month, year, ten year period) Data mining operations  finding / visualizing clusters  seeking association rules

9. 9 Seismo-Surfer Functionality (2) Remote data sources integration (e.g. from the web).  Example: only summaries of seismic data could be stored locally and additional data could be loaded, from the remote (web) source, on demand Phenomena extraction  Example: automatic extraction of semantics from stored data, such as othe main shock and opossible intensive aftershocks in shock sequences

10. 10 Seismo-Surfer Current Status (1) A prototype has been implemented using Oracle (9i DB & Spatial Data Cartridge) and Java technologies. Two web sources have been integrated and the local database is auto-updated  Greek events (source: Inst. of Geodynamics @ the Nat’l Observatory of Athens www.gein.noa.gr )  Global events (source: US Geological Survey www.usgs.gov ). Extra map layers with geographical entities of Greece (populated places, islands etc.) have been also integrated.  (source: US NIMA www.nima.mil )

11. 11 Seismo-Surfer Current Status (2) Current functionality includes  Spatiotemporal Queries (exploiting the R-tree indexing technique):  Range queries (epicenters in a region)  Nearest-Neighbor Queries (epicenters closest to a point on the map)  Distance Queries (epicenters at a distance lees than X)  Closest-Pair Queries (epicenters closest to Greek cities) (cont’d)

12. 12 Seismo-Surfer Current Status (3) (cont’d)  Data Mining Operations  Currently, a single clustering algorithm (k-means)  Various visualization features  Maps, plots and GUI tools that assist the user to the query formulation process and allow viewing the selected or analyzed data in a number of different ways. Screenshots …

13. 13 1) Spatio-temporal queries

14. 14 1a) Closest-pair queries

15. 15 2) Clustering

16. 16 3) Plotting facilities

17. 17 Future Work Data warehouse functionality  summarized views of data  spatial (e.g. province, country, continent)  temporal (e.g. month, year, ten year period)  aggregations stored locally; detailed data fetched from web sources, on demand More data mining operations  more clustering techniques  algorithms for classification and correlation rules More data sources and layers  ‘smart’ filters for feeding local DB  Semi-structured data?

18. 18 Conclusions Seismo-Surfer is a prototype data management and mining system for seismic data Combines latest research trends in database management, data warehousing and data mining Integrates data from remote (web) sources Two versions will be available soon:  A desktop version of full functionality  A web interface (light version) For more information: http://isl.cs.unipi.gr/seismo/