Toolkit for Agent-based Knowledge Extraction (TAKE™)

KBSI used a hybrid approach combining ontology engineering methods with cutting-edge knowledge discovery techniques to extract, analyze, and map ontologies from knowledge and data sources.  The TAKE™ technology helps users to rapidly and cost effectively analyze, redesign, integrate and/or re-engineer their enterprise systems.

In the early phase of the initiative, KBSI established a novel TAKE™ ontology reuse and application method, designed innovative ontology analysis and ontology extraction algorithms, and designed the TAKE™ architecture.  These innovations include the novel application of information fusion techniques for aggregated ontology similarity assessment and mapping the application of advanced knowledge discovery techniques for automated ontology extraction and mapping from multi-source text data.  A demonstration of a prototype TAKE™ software tool was also demonstrated on a focused, high payoff Navy transition application scenario.  The TAKE™ technology provides innovative solutions that address the problems associated with rapidly designing, developing, and deploying large scale knowledge based applications.  KBSI’s overall approach in the initiative conceptualized and validated a framework and a methodology for sustainable knowledge management that encompasses the entire knowledge life cycle:  capture/discovery, representation, analysis, validation, storage, retrieval, (in-context) delivery, and evolution over extended periods of time.

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Hybrid Framework for Information Visualization Enablers (HI-FIVE)

HI-FIVE is a novel model-based, “no-programming required” approach to information visualization.  The tool provides an extendible framework for rapidly developing, configuring, and managing data displays, enabling you to better understand “system of systems” data.

An important challenge for any enterprise, particularly one as large as the Department of Defense, is making the most of your data:  how to achieve true enterprise information integration in a manner that enables access to data from multiple, often divergent domains.  In meeting this challenge, the DoD is integrating new and legacy systems into federated “systems of systems.”  Such an approach necessitates that data from these multiple domains also be integrated—i.e., actionable across all domains—and that it be flexible enough to be used in many, unanticipated ways.

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Ontology-Driven Integration Framework (ODIF)

Ontology-driven Integration Framework (ODIF) automates the sharing and integration of information among different organizations.  ODIF applies a common ontology for integrating diverse data sources and uses knowledge extraction techniques and ontology analysis methods to extract knowledge from distributed, unstructured text sources.

An important challenge for any large enterprise is effectively sharing and integrating information among the organizations and diverse systems that make up the enterprise.  If you’re the U.S. Air Force or the Missile Defense Agency (MDA), enterprises of staggering size, sweep, and application and systems diversity, this challenge is particularly complex.

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Disaster Case Management Platform (DCP)

The Disaster Case Management Platform (DCP) supports the life cycle of disaster case management, providing advanced, customizable reporting and analytics for resource optimization, templates and statistical parameter estimation for different disaster scenarios.

The sought after level of disaster case management includes an IT platform that serves multiple functions, including case management and resource database capabilities.  The IT system should automate and support all case management functions, including intake, screening, assessment, plan development, referrals, recovery plan goal tracking, and closeout.  It should also support program administration, monitoring, and reporting by providing compliance and performance monitoring reports to ACF, contractor management, and case management supervisors.  Recent disaster relief operations have highlighted the need for increased federal involvement in relief operations planning and execution.  Specifically, the Administration for Children and Families (ACF), Office of Human Services Emergency Preparedness and Response (OHSEPR) has been charged with providing leadership in human services emergency preparedness and response.  A particular mandate for the ACF, despite recent technical and financial commitments from the federal government, is for further improvements in disaster relief case management.

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Success Story: Comprehensive Blood Supply Management

Effective emergency response requires more than getting equipment and personnel to the scene.  As important is determining what supplies are available and where they are available, as well as ensuring that required supplies are staged and deployed in a manner that meets the needs of the situation and any contingencies that might arise.  Providing this kind of responsiveness requires two important capabilities:  an awareness of what supplies are available, and the ability to communicate, easily and comprehensively, the status of those supplies.  As any supply chain manager will tell you, inventory planning and awareness is critical to successful emergency response.

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Framework for Interoperability of Executable Architectures (FIEA)

FIEA is a language, tool framework, and methodology that enables the Air Force and DoD to share data among the many vendor specific tools and applications used in global joint service and multinational operations.

These tools, at best, provide a means for government agencies and their contractors to document their enterprise architectures:  they don’t facilitate the model-based analysis of architectures, a critical step in improving systems capability, acquisition, and investment returns.

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Military Health Data Mining Algorithms Library (M-HDML)

The Military Health Data Mining Algorithms Library (M-HDML) applies data mining technologies and techniques to the storage and retrieval of patient data, helping doctors in the DoD’s vast medical health system (MHS) to more accurately diagnose their patients.

In our increasingly data-centric world, data mining technologies are being enlisted for a wide variety of uses:  from retail sales, to video gaming, to, most recently, combating terrorism.  The staggering amount of data has improved the stock of intelligent data mining systems and knowledge discovery techniques that help users extract meaningful information from enormous data sets.  In the industrial arena, more and more organizations are investing in data mining techniques (software and hardware) as a means for gaining profitable business insights from their huge central transactional databases.  The Gartner group estimates that the use of data mining applications will increase from less than 5% currently to 80% over the next decade.*

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Superiority Through Better Decision Making (SUPERCISION™)

Superiority Through Better Decision Making (SUPERCISION™) uses data mining, Bayesian nets, situation theory, and commercial gaming technologies to support the assessment and improvement of decision making skills in training systems.  SUPERCISION™ methods and tools improve scenario-based training and reduce the time and effort needed to create tailored training scenarios.

A frequently quoted maxim from the Army’s 100-5 Operations Field Manual states:  “Effective decision making combines judgment with information as an element of combat power:  it requires knowing if to decide, when to decide, and what to decide.”

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