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An Approach to Data Center-Based KDD of Remote Sensing DatasetsThe data explosion in remote sensing is straining the ability of data centers to deliver the data to the user community, yet many large-volume users actually seek a relatively small information component within the data, which they extract at their sites using Knowledge Discovery in Databases (KDD) techniques. To improve the efficiency of this process, the Goddard Earth Sciences Distributed Active Archive Center (GES DAAC) has implemented a KDD subsystem that supports execution of the user's KDD algorithm at the data center, dramatically reducing the volume that is sent to the user. The data are extracted from the archive in a planned, organized "campaign"; the algorithms are executed, and the output products sent to the users over the network. The first campaign, now complete, has resulted in overall reductions in shipped volume from 3.3 TB to 0.4 TB.
Document ID
20010029447
Acquisition Source
Goddard Space Flight Center
Document Type
Preprint (Draft being sent to journal)
Authors
Lynnes, Christopher
(NASA Goddard Space Flight Center Greenbelt, MD United States)
Mack, Robert
(NASA Goddard Space Flight Center Greenbelt, MD United States)
Wharton, Stephen W.
Date Acquired
August 20, 2013
Publication Date
January 1, 2001
Subject Category
Earth Resources And Remote Sensing
Meeting Information
Meeting: Mining Scientific Datasets
Location: Chicago, IL
Country: United States
Start Date: April 7, 2001
Distribution Limits
Public
Copyright
Work of the US Gov. Public Use Permitted.

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