Title :
Geo-temporal Visualization of Information Collected from Large Databases Using the Time-Based COCOM Operational Picture (TIMECOP) Server
Author :
Roe, Kevin P. ; Murphy, Maria ; Schmidt, Jeff
Author_Institution :
Maui High Performance Comput. Center (MHPCC), Kihei, HI, USA
Abstract :
The Time-Based COCOM Operational Picture (TIMECOP) system provides the ability to visualize events over geographic locations as a function of time. It allows the user to discover geo-temporal trends, patterns, and behaviors over very large regions down to specific sites as well as user-defined time periods. This data mining capability has the capacity to make trend analysis possible for users who would have found it otherwise impossible to manually extract the necessary information from a large database and/or a merged collection from multiple data sources. Although the TIMECOP system was initially tuned to operate on a single large database, it is actually data agnostic and has been modified to serve the needs of other users operating on data from different sources. Users connect either to remote or local TIMECOP servers depending on their needs and restrictions. The database is selected from a pull-down menu and the query options matching the database´s contents are dynamically populated. The user makes their query choices and submits the request. The TIMECOP server passes the query to the respective database and returns a formatted Keyhole Markup Language (KML) file or network link for GoogleEarth to display. Users can examine the data statically or in a movie-like fashion, which allows them to engage in geo-temporal trend analysis. Users may then refine the query parameters and resubmit if necessary. The TIMECOP system can operate under low bandwidth conditions, allowing it to transmits query results via a network link to the user´s GoogleEarth client. Depending on the query, the resulting KML file transmitted is typically in the kB range. TIMECOP users can further modify their queries to limit the number of results returned if they are in a low bandwidth environment.
Keywords :
Internet; XML; client-server systems; data visualisation; geophysical image processing; knowledge acquisition; pattern matching; query processing; search engines; GoogleEarth; KMI file; TIMECOP server; data mining; geographic location; geotemporal visualization; information extraction; keyhole markup language; large database; pull down menu; query options matching; time based COCOM operational picture server; user defined time period; Data mining; Databases; Earth; High performance computing; Magneto electrical resistivity imaging technique; Web server;
Conference_Titel :
DoD High Performance Computing Modernization Program Users Group Conference (HPCMP-UGC), 2009
Conference_Location :
San Diego, CA
Print_ISBN :
978-1-4244-5768-7
DOI :
10.1109/HPCMP-UGC.2009.80