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Perspectives on the Need for Semantic

Technology

James Milligan

Information Directorate Air Force Research Laboratory

James.Milligan@rl.af.mil

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Presentation Outline

• Provide some examples of military problems and needs ripe for semantic technology

• Describe some AFRL activities making use of semantic technology as part of the solution

• Conclusions

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Heterogeneous EnterpriseProblems

• Achieving and maintaining systems interoperability

– Incompatible data, data models, services, and applications.

• Challenges exist in sharing information across domains

– Insufficient information sharing capabilities that allow effective information exchange across multiple communities of interest, security enclaves, organizational boundaries, and infrastructures.

• Policy conflicts can hamper efficiency and effectiveness of joint and coalition operations

– Insufficient means to encode policies for semi-autonomous interpretation, negotiation, enactment, and enforcement.

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Heterogeneous EnterpriseNeeds

• Systems that interoperate (even in the face of change)

– Compatible data, data models, services, and applications.

• Cross-domain information sharing

– Information sharing capabilities that allow effective information exchange across multiple communities of interest.

• Policy specification and enforcement

– Tools and mechanisms to encode policies for semi-autonomous interpretation, negotiation, enactment, and enforcement.

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Policy Enforced Interoperable Communities of Interest

Theater Region (PACOM)Region (PACOM)

COIInformation

Space

COIInformation

Space

COIInformation

Space

Region (NORTHCOM)

COIInformation

Space

Info

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Situational AwarenessProblems

• Maintaining situational awareness is difficult if the necessary collection assets cannot be rapidly deployed and connected

– Inability to autonomously manage and network theatre assets for rapid situational awareness.

• Correlating and integrating vast amounts intelligence data remains a hard problem

– Particularly as new sensor systems and platforms come on-line, it is difficult to effectively correlate, disambiguate, deconflict and combine sensor and human intelligence data into a common contextual model.

• Human interpretation of intelligence information is time consuming and sometimes error-prone

– Insufficient ability to rapidly interpret vast amounts of intelligence information.

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Situational AwarenessNeeds

• Enabling situational awareness

– Ability to autonomously manage and network theatre assets for rapidly achieving situational awareness.

• Intelligence data fusion

– Ability to effectively correlate, disambiguate, and combine sensor and human intelligence data into a common context and information model.

• Rapid interpretation of intelligence

– Ability to rapidly interpret vast amounts of intelligence information.

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Intelligence Collection and Analysis

Enable

Fuse

Interpret

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Effects-Based OperationsProblems

• Ensuring that critical command and control systems continue to operate as needed

– Information systems require a high level of human intervention to keep them operational during mission preparation and execution.

• It is difficult to synchronize the application of diverse, distributed forces in time-critical situations

– Execution management capabilities are challenged in near real-time conditions in order to dominate an adversary and achieve the desired effects.

• Rapidly assessing that combat operations are achieving the desired effects is a challenge

– Real-time effects-based assessment of combat operations is problematic.

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Effects-Based OperationsNeeds

• Command and control systems resource management

– Self-aware systems that can learn, adapt, and heal themselves.

• Rapid employment of agile forces

– Near real-time, dynamic synchronization of the employment of distributed forces to dominate an adversary and achieve desired effects.

• Real-time effects assessment

– Provisioning of real-time effects-based assessment of combat operations.

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C2, Synchronization, Assessment

Targeting Decision

CAOC

Collaboration

NCES MessagingService

NCES CollaborationService

SubscribersCAOC

BDA

Notification

ConstellationNet

Semantically Tagged Info

NCES MessagingService

CAOC – Combined Air and Space Operations Center

NCES – Net-centric Enterprise Services

Intelligence Report

ENEMY

TANK

Weapons Effects AssessmentWeapons Effects Assessment

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AFRL Semantic WebTechnologies & Applications

• Enabling Technologies

– Ontologies

– Knowledge Bases

– Artificial Intelligence

– Expert Systems

– Intelligent Agents

– Machine Inferencing, Reasoning and Learning

– Formal Methods

– W3C Standards, Protocols, and Reference Implementations

• Defense Applications

– Net-Centric Operations (e.g., NCES)

• Service Discovery, Composition, Mediation, Workflow Orchestration, and Execution

– Natural Language Processing

– Systems and Information Modeling, Integration, and Interoperability

– Knowledge Acquisition/Representation

– Cognitive Systems

– Modeling and Simulation

– Policy Representation and Enforcement

– Collaboration

– Cross-domain Information Sharing

– Resource Management

– Effects Based Operations

– Adversarial Modeling/Cyber Operations

– Decision Support/Planning/Predictive Environments (e.g., CPE)

– Multi-Platform/Source Intelligence Fusion

– Homeland Security

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Representative AFRL Semantic Research and Applications

• Information Transformation

– Semantic Interoperability

• Anticipatory Environments

– Dynamic Air & Space Effects Based Assessment (DASEA)

• Collaboration

– Distributed enterprise object models

– Integrating Human Centeredness in the Design of Collaborative Systems

• Cross-Domain Information Access (CDIA)

– Foundation technologies

• Defensive Cyber Operations

– Cyber Situational Understanding (Event Pattern Ontologies SBIR)

• NETWAR: Strategic Attack Prediction and Detection

• Command and Control Resource Management System

• Link Discovery & Pattern Learning

• Heterogeneous Urban RSTA—Reconnaissance, Surveillance, Target Acquisition—Team (HURT)

• SIGINT Sensor Management

• Semantic-based Policy Enforcement

• Effects Based Operations

– Ontology for Scenario Generation SBIR

• NeXt Generation (XG) Program

– OWL Policy Language Development

• Command and Control Mobility Projects

– Intelligent Semantic NOTAM Query Capability

• Formal Methods

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Representative AFRL Efforts Employing Semantic Technologies

• Broad Agency Announcements (BAAs)

– Semantic Interoperability

– Rapid Processing of Intelligence Data

– Commander’s Predictive Environment (CPE)

– Infospace Concept Exploration and Development

– Multi-Platform SIGINT Fusion and ISR Management

– Tangram: A Fully Automated, Continuously Operating, Intelligence Analysis Support System

– Intelligence Fusion for Targets-Under-Trees

• FY06 Small Business Innovative Research (SBIR) Program topics:

– AF06-047 Semantic Interoperability of C2 Tools and Technologies

– AF06-049 Real-Time Effects Assessment Management System

– AF06-052 Semantically Correct Interoperability of Executable Architectures

– AF06-053 Knowledge-based Technologies to Support Predictive Mission Awareness

– AF06-060 Enabling Monitoring and Analysis of Concept-Based Event Information in Text

– AF06-061 Multi-INT Ontology Mediation Services

– AF06-066 Systems-of-Systems Data Utilization Patterns

– AF06-077 Command Decision Support and Explanation from Fused Structured and Unstructured Information Sources

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Conclusions

• Semantic technology holds great promise in addressing many of the problems and needs identified

• Additional investments are needed to mature the technology and make it easier to use and deploy in military applications

• An incremental approach toward widespread adoption seems likely – some semantic technologies will gain traction sooner than others

• We (academia, industry, government) need to do it together, and progress is rapidly being made from a historical perspective