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Information Technology and Systems Center
University of Alabama in Huntsville
S339 Technology Hall,
Huntsville, AL 35899
(256) 824-6868
info@itsc.uah.edu
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Data Mining and Image Processing Toolkits
The Algorithm Development and Mining System (ADaM) developed by the Information Technology and Systems Center at the University of Alabama in Huntsville is used to apply data mining technologies to remotely-sensed and other scientific data. The mining and image processing toolkits consist of interoperable components that can be linked together in a variety of ways for application to diverse problem domains. ADaM has over 100 components that can be configured to create customized mining processes. Preprocessing and analysis utilities aid users in applying data mining to their specific problems. New components can easily be added to adapt the system to different science problems.

The 4.0 release of ADaM is a significant architectural paradigm shift from previous versions. The latest version (4.0.2) (see release note) provides a solution that easily supports the integration of 3rd party algorithms and the reuse of ADaM components by other systems. ADaM 4.0.2 provides this support through the use of autonomous components in a distributed architecture. Each component is provided with a C, C++, or other application programming interface (API), an executable in support of generic scripting tools (e.g. Perl, Python, shell scripts) and eventually web service interfaces to support web and grid applications. ADaM 4.0.2 components are general purpose mining and image processing modules that can be easily reused for multiple solutions and disciplines. These components are well positioned to address the needs for distributed mining and image processing services in web and grid applications.

Component Architecture
ADaM's component architecture is designed to take advantage of emerging computational environments such as the Web and information Grids. Individual ADaM operations can execute in a stand-alone fashion, facilitating their use in distributed and parallel processing systems. The operations - organized as toolkits - provide pattern recognition, image processing, optimization, and association rule mining capabilities. Components are packaged in several ways, including C/C++ libraries, executables, and Python modules. Multi-interface component packaging facilitates rapid prototyping and efficient, performance-critical data mining application development. This approach also facilitates the use of ADaM components by and with third-party analysis and visualization systems.
Distributed Services
ADaM components can be accessed via multiple external interfaces. This flexibility facilitates the implementation of data mining and image processing components as Web and Grid services. Consistent and well documented execution protocols support the incorporation of ADaM components into applications that are developed using common network-enabled scripting languages such as Perl and Python. The incorporation of data interchange technologies such as the Earth Science Markup Language (ESML) yields distributed interoperability across heterogeneous scientific data sets.
Custom Applications
Custom applications can be generated from the toolkits of mining and image processing components, perhaps combined with other specialized software modules. One example is the use of ADaM to detect tropical cyclones and estimate their maximum sustained winds. This operational application uses a combination of general-purpose image analysis modules plus special purpose modules developed specifically for the problem. The near real-time storm information can be viewed on the web at http://pm-esip.nsstc.nasa.gov/cyclone/.
Grid-enabled Services
NASA and the National Science Foundation are actively pursuing computational Grid technologies. ITSC data mining technologies are currently in use in both areas. ADaM is the first data mining application to execute on the NASA Information Power Grid. The ADaM toolkits can be made available as a set of Open Grid Services Architecture components that easily translate to the Grid environment.