A Seismic Data Management and Mining System

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A Seismic Data Management and Mining System
Seismo-Surfer
a tool for collecting, querying, and mining
seismic data
Yannis Theodoridis
University of Piraeus
[email protected]
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Outline of the presentation
Concepts and motivation
The Seismo-Surfer tool
 Architecture
 Functionality
 Current status
Future work
Conclusions
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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)
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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.
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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
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Seismo-Surfer Architecture
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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
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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
o the main shock and
o possible intensive aftershocks
in shock sequences
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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 )
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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)
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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 …
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1) Spatio-temporal queries
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1a) Closest-pair queries
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2) Clustering
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3) Plotting facilities
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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?
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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/
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