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Model-based Communication Networks, Valued Information at the Right Time (VIRT) & Rich Semantic Track (RST): Filtering Information by Value to Improve Collaborative Decision-Making. Project Report on CEC Collaboration Rick Hayes-Roth hayes-roth@nps.edu June 15, 2007. Outline.

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Project report on cec collaboration rick hayes roth hayes roth@nps edu june 15 2007

Model-based Communication Networks, Valued Information at the Right Time (VIRT) & Rich Semantic Track (RST):Filtering Information by Value to Improve Collaborative Decision-Making

Project Report on CEC Collaboration

Rick Hayes-Roth

hayes-roth@nps.edu

June 15, 2007


Outline
Outline

  • Overall Vision: Model-based Communication Networks, VIRT, and Rich Semantic Track

  • CEC/VIRT Project Results and Accomplishments

  • Rich Semantic Track Definition and Influence on Community Developments

  • Semantic Modeling and Condition Monitoring: Making Information Delivery More Precise and Reducing Work Load

  • Opportunities for Further Collaboration


Outline1
Outline

  • Overall Vision: Model-based Communication Networks, VIRT, and Rich Semantic Track

  • CEC/VIRT Project Results and Accomplishments

  • Rich Semantic Track Definition and Influence on Community Developments

  • Semantic Modeling and Condition Monitoring: Making Information Delivery More Precise and Reducing Work Load

  • Opportunities for Further Collaboration


Overall vision model based communication networks virt and rich semantic track
Overall Vision: Model-based Communication Networks, VIRT and Rich Semantic Track

Common Track Semantics

State-full Network

Global

Information

Grid

COIs

COIs

Future

Present

Present

Present

Future

Shared World Models

Future

Past

Past

Present

Future

Past

Past


Overall vision model based communication networks virt and rich semantic track1
Overall Vision: Model-based Communication Networks, VIRT and Rich Semantic Track

Common Track Semantics

State-full Network

Global

Information

Grid

Valued Bits

Valued Bits

Future

Present

Present

Present

Future

Shared World Models

Future

Past

Past

Present

Future

Past

Past


Outline2
Outline Rich Semantic Track

  • Overall Vision: Model-based Communication Networks, VIRT, and Rich Semantic Track

  • CEC/VIRT Project Results and Accomplishments

  • Rich Semantic Track Definition and Influence on Community Developments

  • Semantic Modeling and Condition Monitoring: Making Information Delivery More Precise and Reducing Work Load

  • Opportunities for Further Collaboration


Cec virt project key results
CEC/VIRT Project Key Results Rich Semantic Track

  • Advanced theory and implementation of Valued Information at the Right Time (VIRT) and Rich Semantic Track (RST)

    • Demonstrated significant reductions in bandwidth from 2-5 orders of magnitude in initial studies to 45-90% in CEC-specific simulated message streams

  • Created research opportunities for NPS faculty and students

  • Created research and development initiatives with government and industry

  • Developed simulation framework for advanced studies of VIRT and RST


Cec virt project results 1
CEC/VIRT Project Results (1) Rich Semantic Track

  • Prepared/published/presented several papers

    • “Model-based Communication Networks and VIRT: Filtering Information by Value to Improve Collaborative Decision-Making”

    • “Towards a Rich Semantic Model of Track: Essential Foundation for Information Sharing”

    • “Two Theories of Process Design for Information Superiority: Smart Pull vs. Smart Push”

    • VIRT Technical Architecture Specification (Draft)

    • “Hyper-Nodes for Emerging Command and Control Networks: The 8th Layer” (with Alex Bordetsky)

    • “Model-Based Communication Networks and VIRT: Orders of Magnitude Better for Information Superiority”

    • “Decision Making in Very Large Networks” (with Peter Denning)

    • “Semantic Reasoning for Adaptive Management of Telecommunications Networks” (with J. C. Hoag)

  • Established VIRT as key focus of W2COG

    • VIRT driving various groups’ efforts


Cec virt project results 2
CEC/VIRT Project Results (2) Rich Semantic Track

  • Recruited & mentored three NPS thesis students

  • Mentoring two NPS PhD students

  • Helped PACOM start up CMA JCTD around sharing of rich track information; leading design and development of the CMA data model

  • Advising Joint Track Management (JTM) Architecture Working Group

  • Acquired workstation & CEC simulation data

  • Completed first computational model of CEC-VIRT concepts in thesis research


Cec virt project results 3
CEC/VIRT Project Results (3) Rich Semantic Track

  • Designed and implemented CEC-VIRT simulation framework for continuing test and experimentation

  • Conducted computational analysis of CEC simulated message streams

  • Mapped CEP-to-Track-User message elements to abstract Rich Semantic Track model

  • Initiated design and development of Semantic Web representations of RST

  • Designed expressions of VIRT Conditions of Interest using Semantic Web technologies in CEC context

  • Initiated design and development of formalized theory of RST

  • Defined initial measures of performance for evaluating VIRT applications


Virt implementation and testing
VIRT Implementation and Testing Rich Semantic Track

  • Described VIRT Product Line Architecture approach

  • Built collaboration with industry to generate a draft technical architecture for VIRT

  • Hayes-Roth paper showed 5 orders of magnitude reduction in bandwidth using Smart Push Implementation

  • LCDR Acevedo thesis describing application of VIRT concepts in context of the CEC -- Under modeling assumptions, Theory 2 Smart Push model showed a decrease of nearly 200 times the bandwidth of Theory 1, Smart Pull model


Outline3
Outline Rich Semantic Track

  • Overall Vision: Model-based Communication Networks, VIRT, and Rich Semantic Track

  • CEC/VIRT Project Results and Accomplishments

    • Drill-down on Analysis of CEC Message Streams

  • Rich Semantic Track Definition and Influence on Community Developments

  • Semantic Modeling and Condition Monitoring: Making Information Delivery More Precise and Reducing Work Load

  • Opportunities for Further Collaboration


Cec virt message stream analysis
CEC/VIRT Message Stream Analysis Rich Semantic Track

  • Simulated message streams provided by JHU/APL

  • Focus on application of VIRT at an intermediary node (“VIRT Track User”) between the CEC network and the general GIG network

  • Value determined by “GIG User” Conditions of Interest (COIs) relating to expected position and velocity, track identification, and engagement status

  • Computed bit traffic reduction of 45-90% in short duration, highly dynamic air tracking scenarios

  • Demonstrated capability to “tune” bit traffic flows based on user-defined thresholds in accuracy of estimations


Cec virt message stream scenarios
CEC/VIRT Message Stream Scenarios Rich Semantic Track

  • Air Target Tracking scenario

    • Unclassified message stream provided by JHU/APL

    • XML-formatted RTTS messages, similar in content to CEP-to-Track-User messages, but not in strict conformance to the Interface Design Document

    • 10-minute duration

  • Target Ring scenario

    • Classified message stream provided by JHU/APL

    • Formatted text messages conforming to the CEP-to-Track-User Interface Design Document

    • 11.25-minute duration


Operational assumptions both scenarios
Operational Assumptions Rich Semantic Track(both scenarios)

  • Detected aircraft are initially behaving in accordance with expectations

  • Intermediary node (Track User) between the CEC network and the general user (GIG User) shares the same expectations of target behavior as the GIG User

  • Track User node is given knowledge of GIG User COIs

  • Only a significant deviation from expected behavior is considered “valued information”

Under these assumptions, what portion of the message stream is passed to the user node?


Cec virt conditions of interest both scenarios
CEC/VIRT Conditions of Interest Rich Semantic Track(both scenarios)

  • Significant change in expected motion of air tracks based on decision thresholds for the magnitude of change in expected position and expected velocity

  • Significant change in Track ID information (e.g., from FRIEND to HOSTILE)

  • Significant change in Track IFF information (e.g., change in IFF mode responses)

  • Start and end of engagements

  • Assumption/Operational Decision: No need to send CEC network-specific Cooperating Unit, Time, and Status messages


Air target tracking scenario results

Valued bits made up 7% of the total bits transmitted – bit traffic can be reduced by 93% if only valued bits are sent!ru

Air Target Tracking Scenario Results

* From RTTS XML message stream

** Dead Reckoning thresholds of 100m and 10m/sec


Air target tracking scenario discussion
Air Target Tracking Scenario traffic can be reduced by 93% if only valued bits are sent!ruDiscussion

  • Results used position and velocity information in all 3 dimensions

  • If initial shared awareness is assumed, only 1 of the 18 Track ID messages needed to be sent (change from ASSUMED FRIEND to UNKNOWN)

  • None of the 552 Cooperating Unit messages needed to be sent (CEC domain only)

  • None of the 121 Track IFF messages needed to be sent (information of significance provided in the Track ID message)

  • Portion of Track Data messages sent depended on criteria applied (position or velocity) and threshold setting

    • 92% reduction in Track Data bit traffic at 100m position threshold and 10m/sec velocity threshold


Target ring scenario results

Valued bits made up 55% of the total bits transmitted – bit traffic can be reduced by 45% if only valued bits are sent!

Target Ring Scenario Results

* From RTTS XML message stream

** Dead Reckoning thresholds of 100m and 10m/sec


Target ring scenario discussion
Target Ring Scenario bit traffic can be reduced by 45% if only valued bits are sent!Discussion

  • Results used position and velocity information in all 3 dimensions (east/west, north/south, and altitude)

  • Passed initial Track ID messages and changes in reported attributes

    • Refinements to Track ID COIs may be possible

  • Only sent 5 of 75 Track IFF messages, representing conditions raising suspicion about the track

  • None of the 601 Cooperating Unit messages, 136 Status messages, and 62 Time messages needed to be sent (CEC domain only)

  • Portion of Track Data messages sent depended on criteria applied (position or velocity) and threshold setting

    • 44% reduction in Track Data bit traffic at 100m position threshold and 10m/sec velocity threshold


Cec message stream analysis conclusions
CEC Message Stream Analysis bit traffic can be reduced by 45% if only valued bits are sent!Conclusions

  • Can achieve significant reduction in bit traffic from attention to user information needs (COIs)

  • Demonstrated mechanisms for enabling CEC message traffic to be filtered for non-CEC users

  • Opportunity for further research into user-specified COIs and message processing using more of the message content (e.g., certainty and accuracy data)


Outline4
Outline bit traffic can be reduced by 45% if only valued bits are sent!

  • Overall Vision: Model-based Communication Networks, VIRT, and Rich Semantic Track

  • CEC/VIRT Project Results and Accomplishments

  • Rich Semantic Track Definition and Influence on Community Developments

  • Semantic Modeling and Condition Monitoring: Making Information Delivery More Precise and Reducing Work Load

  • Opportunities for Further Collaboration


Rich semantic track model
Rich Semantic Track Model bit traffic can be reduced by 45% if only valued bits are sent!

  • Need practical ontologies for important domains

  • Tracks are common information elements in numerous military and non-military domains

    • A common “informal” concept in military operations

    • Now vital in multiple domains: aircraft, ships, vehicles, people, cargo, …

    • Semantic hub + translator generators => information sharing

  • Provides vocabulary for expressing COIs

  • Provides logical constructs for evaluating COIs


Rich semantic track rst
Rich Semantic Track (RST) bit traffic can be reduced by 45% if only valued bits are sent!

CMA

Maritime

Information

Exchange Model

CEC

Track

Messages

  • Rich Semantic Track

  • conceptual hub for interchange and automated

  • reasoning

Joint

Track

Management

Data Model

Other

Track

Data Models


The rich semantic track model
The Rich Semantic bit traffic can be reduced by 45% if only valued bits are sent!Track Model

  • Track

    • Beliefs

    • Identity and Characteristics

    • Dynamic State at Time T

    • History of states (past “track”)

    • Predicted states (future “track”)

    • Meta-Information (applicable to each element of belief)

    • Evidence

    • Inferences

    • Error and uncertainty estimates

    • Temporal qualifications

    • Spatial qualifications

The top-level conceptual hierarchy for Track.

The full hierarchy has more than 125high level concepts.


Cec virt project
CEC/VIRT Project bit traffic can be reduced by 45% if only valued bits are sent!

  • Investigated mapping of CEC track data to RST conceptual model

  • Constructed various RST representations for software and web-based implementations

    • Formal logic representation for automating mappings across track data models

    • Semantic Web representations for web-based data interchange and machine reasoning

  • Constructed various web-based expressions of COIs


Rich semantic track influences on community developments
Rich Semantic Track: bit traffic can be reduced by 45% if only valued bits are sent!Influences on Community Developments

  • Defines core semantic model for Track information combining Beliefs and Meta-Information on precision and certainty

    • Basis for vocabulary of VIRT Conditions of Interest

    • Basis for interchange across multiple track data models

    • Basis for formal logic for track computation

  • Advising Comprehensive Maritime Awareness (CMA) JCTD for development of the Maritime Information Exchange Model (MIEM)

  • Advised the Joint Track Management (JTM) Enterprise Architecture Working Group on data modeling of beliefs and pedigree


Miem objectives
MIEM Objectives bit traffic can be reduced by 45% if only valued bits are sent!

Dynamic nature of all quantities (potentially any belief/value can vary in time)

Inexact information (“roughly 30 feet long”)

Relative information (“a mile from the leader of XYZ”)

Conditionals (“all facilities open on Thursdays”)

Complex queries (“return last five ports of call for vessels flying Chinese of Korean flags and within 3 days of US costal waters”)

Pedigree (“position was derived from AIS message A, ELINT data B, and HUMINT source C, using inference rule D”)

Belief conditions (“value is considered 85% reliable”, “value was provided by source S”, etc.)

Behaviors, states & histories (“the events make up an overall fishing voyage”)

  • Share actionable maritime intelligence in a net-centric way:

    • Simple/raw data exchange

    • Fusion output representation

    • Advanced analytics support

  • Establish unambiguous maritime lexicon that:

    • Supports communication among data providers and consumers

    • Embodies broad expertise covering the extent of the maritime domain

    • Leverages existing models and knowledge bases

  • Enable communications from/with future services and capabilities

    • Permit extension to more sophisticated data without change to existing systems

    • Import partners’ databases and export to them with efficient translators


Levels of value added information
Levels of Value Added Information bit traffic can be reduced by 45% if only valued bits are sent!


Principal elements of miem
Principal Elements of MIEM bit traffic can be reduced by 45% if only valued bits are sent!

  • Key Domain Entities

    • Conveyance/Vessel

    • Person/Crew/Passenger

    • Cargo & Facilities

    • Measurements: Time, Position, Length, Weight, …

  • Key Secondary Concepts

    • Life-cycle: States, Transitions, Voyages, Epochs

    • Of-interest

    • Event

    • Anomalies & Threats

  • Extensive & Universally Applicable Meta-data

    • Source, Confidence, Alternatives, Pedigree, Caveats, …

    • Past, Present & Future

  • Universal Extensibility & Restriction

    • All classes can be augmented or simplified

  • Conceptual model in modular XML schemas


File type hierarchy of miem
File & Type Hierarchy of MIEM bit traffic can be reduced by 45% if only valued bits are sent!


Basis for further research development and experimentation
Basis for Further Research, Development and Experimentation bit traffic can be reduced by 45% if only valued bits are sent!

  • Refine the RST model based on applications in CEC, CMA, and JTM domains

  • Continue development of a higher order abstract formalization of RST (formal theory of Track) for extended reasoning capabilities and cross-domain mappings

  • Refine expressions of RST concepts using Semantic Web standards to promote data interchange and automated interpretation in the GIG architecture

  • Continue integration of software implementations of RST into VIRT/CEC simulation framework for test and experimentation


Outline5
Outline bit traffic can be reduced by 45% if only valued bits are sent!

  • Overall Vision: Model-based Communication Networks, VIRT, and Rich Semantic Track

  • CEC/VIRT Project Results and Accomplishments

  • Rich Semantic Track Definition and Influence on Community Developments

  • Semantic Modeling and Condition Monitoring: Making Information Delivery More Precise and Reducing Work Load

  • Opportunities for Further Collaboration


Semantic modeling and condition monitoring
Semantic Modeling bit traffic can be reduced by 45% if only valued bits are sent!and Condition Monitoring

  • Strong semantic representations of Track data improve automated search, information filtering and reasoning

  • Improved computer interpretation and processing of data provides better information products and reduces human processing load

  • Semantics of military orders implies critical conditions of interest – automated derivation of COIs from orders creates valued information flows


Condition monitoring is key
Condition Monitoring is Key bit traffic can be reduced by 45% if only valued bits are sent!

  • Conditions of Interest (COIs)

    • Computable expressions (“continuous queries”)

    • Describe critical assumptions (like CCIRs)

    • Depend on operator’s evolving context

      • Usually reflects phase of a mission & current status

  • High-value events are detected

    • Data describing the event match the COI

    • The event is “news”

    • The COI assures the event is still “relevant”

    • Bits reporting the event flow with priority

  • Low-value data does not flow

    • Generally relevant data not matching a COI

    • Repeated and redundant data, not newsworthy


Outline6
Outline bit traffic can be reduced by 45% if only valued bits are sent!

  • Overall Vision: Model-based Communication Networks, VIRT, and Rich Semantic Track

  • CEC/VIRT Project Results and Accomplishments

  • Rich Semantic Track Definition and Influence on Community Developments

  • Semantic Modeling and Condition Monitoring: Making Information Delivery More Precise and Reducing Work Load

  • Opportunities for Further Collaboration


Opportunities for further collaboration 1
Opportunities for Further Collaboration (1) bit traffic can be reduced by 45% if only valued bits are sent!

  • Recommended next steps for CEC & IWS

    • Develop and implement VIRT principles inside the CEC network and SIAP (e.g., variable length messages sending only message fields that have significantly changed value)

    • Develop & deliver VIRT track data using COIs to demonstrate timely sharing of valued info

    • Spearhead development of rich track model for SIAP

    • Develop enhanced toolkit for and methods for using a rich semantic track model

      • Semantic V&V

      • Interface & service code generators

      • Track storage & query using XML

      • COI specification, event computing, and AAR learning


Opportunities for further collaboration 2
Opportunities for Further Collaboration (2) bit traffic can be reduced by 45% if only valued bits are sent!

  • Recommendation for JTM Enterprise Architecture Working Group

    • Examine MIEM products of the CMA JCTD

    • Identify common concepts and model components

    • Collaborate in developing interchange mechanisms for passing data between the models


Opportunities for further collaboration 3
Opportunities for Further Collaboration (3) bit traffic can be reduced by 45% if only valued bits are sent!

  • Requested Funding for NPS

    • Extend formalization of RST for further experimentation

      • COI expressions

      • Computing with uncertainty

      • Intermediary for automated exchange of data across multiple track representations (MIEM, JTM, others)

    • Research automated derivation of COIs from plans and orders

    • Investigate Web-based techniques to create smart push of valued information from auto-generated COIs


Conclusion
Conclusion bit traffic can be reduced by 45% if only valued bits are sent!

  • New problems & opportunities combine to change our concept of “collaborative communication networks”

  • Humans must use computers to reduce information glut

  • Collaborators need to employ common models to share model state

  • Operators and domain practitioners will use semantic technologies to create and evolve the needed models

  • Each consumer’s plans and beliefs determine the value of information

  • Computers can implement knowledge of decision-makers and current state to determine the flow of bits

  • Significant increases in productivity will result