project report on cec collaboration rick hayes-roth hayes-roth@nps june 15, 2007

# # 11

Model-based Communication Networks, Model-based Communication Networks, Valued Information at the Right Time (VIRT) Valued Information at the Right Time (VIRT)

& Rich Semantic Track (RST):& Rich Semantic Track (RST):

Filtering Information by Value to Improve Filtering Information by Value to Improve

Collaborative Decision-MakingCollaborative Decision-Making

Project Report on CEC CollaborationProject Report on CEC Collaboration

Rick Hayes-RothRick [email protected]@nps.edu

June 15, 2007

# # 22

OutlineOutline

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

CEC/VIRT Project Results and CEC/VIRT Project Results and AccomplishmentsAccomplishments

Rich Semantic Track Definition and Rich Semantic Track Definition and Influence on Community DevelopmentsInfluence on Community Developments

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

Opportunities for Further CollaborationOpportunities for Further Collaboration

# # 33

OutlineOutline






# # 44

COIs

Overall Vision: Model-based Overall Vision: Model-based Communication Networks, VIRT Communication Networks, VIRT

and Rich Semantic Trackand Rich Semantic Track

Past

GlobalInformation

Grid

PastPresent

Future

PresentFuture Present

Past

Present

Future

Past

Future

COIs

Shared World Models

Common Track SemanticsState-full Network

# # 55

Overall Vision: Model-based Overall Vision: Model-based Communication Networks, VIRT Communication Networks, VIRT

and Rich Semantic Trackand Rich Semantic Track

Past

PastPresent

Future

PresentFuture Present

Past

Present

Future

Past

Future

Common Track SemanticsState-full Network

Valued Bits

Value

d Bits

GlobalInformation

Grid

Shared World Models

# # 66

OutlineOutline






# # 77

CEC/VIRT Project Key ResultsCEC/VIRT Project Key Results

Advanced theory and implementation of Advanced theory and implementation of Valued Information at the Right Time (VIRT) Valued Information at the Right Time (VIRT) and Rich Semantic Track (RST)and Rich Semantic Track (RST) Demonstrated significant reductions in Demonstrated significant reductions in

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

Created research opportunities for NPS Created research opportunities for NPS faculty and studentsfaculty and students

Created research and development Created research and development initiatives with government and industryinitiatives with government and industry

Developed simulation framework for Developed simulation framework for advanced studies of VIRT and RSTadvanced studies of VIRT and RST

# # 88

CEC/VIRT Project Results (1)CEC/VIRT Project Results (1) Prepared/published/presented several papersPrepared/published/presented several papers

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

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

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

VIRT Technical Architecture Specification (Draft)VIRT Technical Architecture Specification (Draft) ““Hyper-Nodes for Emerging Command and Control Hyper-Nodes for Emerging Command and Control

Networks: Networks: The 8The 8thth Layer Layer” (with Alex Bordetsky)” (with Alex Bordetsky) ““Model-Based Communication Networks and VIRT: Orders Model-Based Communication Networks and VIRT: Orders

of Magnitude Better for Information Superiority”of Magnitude Better for Information Superiority” ““Decision Making in Very Large Networks” (with Peter Decision Making in Very Large Networks” (with Peter

Denning)Denning) ““Semantic Reasoning for Adaptive Management of Semantic Reasoning for Adaptive Management of

Telecommunications Networks” (with J. C. Hoag)Telecommunications Networks” (with J. C. Hoag)

Established VIRT as key focus of W2COGEstablished VIRT as key focus of W2COGVIRT driving various groups’ effortsVIRT driving various groups’ efforts

# # 99

CEC/VIRT Project Results (2)CEC/VIRT Project Results (2)

Recruited & mentored three NPS thesis Recruited & mentored three NPS thesis studentsstudents

Mentoring two NPS PhD studentsMentoring two NPS PhD students Helped PACOM start up CMA JCTD around Helped PACOM start up CMA JCTD around

sharing of rich track information; leading sharing of rich track information; leading design and development of the CMA data design and development of the CMA data modelmodel

Advising Joint Track Management (JTM) Advising Joint Track Management (JTM) Architecture Working GroupArchitecture Working Group

Acquired workstation & CEC simulation dataAcquired workstation & CEC simulation data Completed first computational model of CEC-Completed first computational model of CEC-

VIRT concepts in thesis researchVIRT concepts in thesis research

# # 1010

CEC/VIRT Project Results (3)CEC/VIRT Project Results (3) Designed and implemented CEC-VIRT simulation Designed and implemented CEC-VIRT simulation

framework for continuing test and experimentationframework for continuing test and experimentation Conducted computational analysis of CEC simulated Conducted computational analysis of CEC simulated

message streamsmessage streams Mapped CEP-to-Track-User message elements to Mapped CEP-to-Track-User message elements to

abstract Rich Semantic Track modelabstract Rich Semantic Track model Initiated design and development of Semantic Web Initiated design and development of Semantic Web

representations of RSTrepresentations of RST Designed expressions of VIRT Conditions of Interest Designed expressions of VIRT Conditions of Interest

using Semantic Web technologies in CEC contextusing Semantic Web technologies in CEC context Initiated design and development of formalized Initiated design and development of formalized

theory of RSTtheory of RST Defined initial measures of performance for Defined initial measures of performance for

evaluating VIRT applicationsevaluating VIRT applications

# # 1111

VIRT Implementation and TestingVIRT Implementation and Testing

Described VIRT Product Line Architecture Described VIRT Product Line Architecture approachapproach

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

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

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

# # 1212

OutlineOutline


CEC/VIRT Project Results and CEC/VIRT Project Results and AccomplishmentsAccomplishments Drill-down on Analysis of CEC Message Drill-down on Analysis of CEC Message

StreamsStreams Rich Semantic Track Definition and Rich Semantic Track Definition and

Influence on Community DevelopmentsInfluence on Community Developments Semantic Modeling and Condition Semantic Modeling and Condition

Monitoring: Making Information Delivery Monitoring: Making Information Delivery More Precise and Reducing Work LoadMore Precise and Reducing Work Load


# # 1313

CEC/VIRT Message Stream AnalysisCEC/VIRT Message Stream Analysis

Simulated message streams provided by Simulated message streams provided by JHU/APLJHU/APL

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

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

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

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

# # 1414

CEC/VIRT Message Stream CEC/VIRT Message Stream ScenariosScenarios

Air Target Tracking scenarioAir Target Tracking scenario Unclassified message stream Unclassified message stream

provided by JHU/APLprovided by JHU/APL XML-formatted RTTS messages, XML-formatted RTTS messages,

similar in content to CEP-to-similar in content to CEP-to-Track-User messages, but not Track-User messages, but not in strict conformance to the in strict conformance to the Interface Design DocumentInterface Design Document

10-minute duration10-minute duration Target Ring scenarioTarget Ring scenario

Classified message stream Classified message stream provided by JHU/APLprovided by JHU/APL

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

11.25-minute duration11.25-minute duration

Track Plot(relative to position of reporting platform)

-150

-100

-50

0

50

100

150

-150 -100 -50 0 50 100 150

East/West Position

No

rth

/So

uth

Po

siti

on

# # 1515

Operational AssumptionsOperational Assumptions(both scenarios)(both scenarios)

Detected aircraft are initially behaving in Detected aircraft are initially behaving in accordance with expectationsaccordance with expectations

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

Track User node is given knowledge of GIG Track User node is given knowledge of GIG User COIsUser COIs

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

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

# # 1616

CEC/VIRT Conditions of InterestCEC/VIRT Conditions of Interest(both scenarios)(both scenarios)

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

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

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

Start and end of engagementsStart and end of engagements Assumption/Operational Decision: No need Assumption/Operational Decision: No need

to send CEC network-specific Cooperating to send CEC network-specific Cooperating Unit, Time, and Status messagesUnit, Time, and Status messages

# # 1717

Air Target Tracking Scenario ResultsAir Target Tracking Scenario Results

CEP-to-CEP-to-Track User Track User Messages*Messages*

Number of MessagesNumber of Messages Number of BitsNumber of Bits

Without Without VIRTVIRT

With With VIRT**VIRT**



Valued Valued Bit RatioBit Ratio

Track DataTrack Data 1,8521,852 141141 2,483,7122,483,712 189,504189,504 0.0760.076

Track IDTrack ID 1818 66 9,2169,216 3,0723,072 0.3330.333

Track IFFTrack IFF 121121 00 42,59242,592 00 0.0000.000

Cooperating Cooperating UnitUnit

552552 00 176,640176,640 00 0.0000.000

Engagement Engagement StatusStatus

00 00 00 00 N/AN/A

StatusStatus 00 00 00 00 N/AN/A

TimeTime 00 00 00 00 N/AN/A

TotalsTotals 2,5432,543 147147 2,712,1602,712,160 192,576192,576 0.0710.071

* From RTTS XML message stream ** Dead Reckoning thresholds of 100m and 10m/sec

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

# # 1818

Air Target Tracking Scenario Air Target Tracking Scenario DiscussionDiscussion

Results used position and velocity information in all 3 Results used position and velocity information in all 3 dimensionsdimensions

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

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

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

Portion of Track Data messages sent depended on Portion of Track Data messages sent depended on criteria applied (position or velocity) and threshold criteria applied (position or velocity) and threshold settingsetting 92% reduction in Track Data bit traffic at 100m position 92% reduction in Track Data bit traffic at 100m position

threshold and 10m/sec velocity thresholdthreshold and 10m/sec velocity threshold

# # 1919

Target Ring Scenario ResultsTarget Ring Scenario Results

CEP-to-CEP-to-Track User Track User Messages*Messages*

Number of MessagesNumber of Messages Number of BitsNumber of Bits





Valued Valued Bit RatioBit Ratio

Track DataTrack Data 15,62515,625 8,7368,736 21,000,00021,000,000 11,741,18411,741,184 0.5590.559

Track IDTrack ID 157157 106106 80,38480,384 54,27254,272 0.6750.675

Track IFFTrack IFF 7575 55 26,40026,400 1,7601,760 0.0670.067

Cooperating Cooperating UnitUnit

601601 00 192,320192,320 00 0.0000.000

Engagement Engagement StatusStatus

6262 44 15,87215,872 1,0241,024 0.0650.065

StatusStatus 136136 00 26,11226,112 00 0.0000.000

TimeTime 6262 00 15,87215,872 00 0.0000.000

TotalsTotals 16,71816,718 8,8518,851 21,356,96021,356,960 11,798,24011,798,240 0.5520.552

* From RTTS XML message stream ** Dead Reckoning thresholds of 100m and 10m/sec

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

# # 2020

Target Ring Scenario Target Ring Scenario DiscussionDiscussion

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

Passed initial Track ID messages and changes in Passed initial Track ID messages and changes in reported attributesreported attributes Refinements to Track ID COIs may be possibleRefinements to Track ID COIs may be possible

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

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

Portion of Track Data messages sent depended on Portion of Track Data messages sent depended on criteria applied (position or velocity) and threshold criteria applied (position or velocity) and threshold settingsetting 44% reduction in Track Data bit traffic at 100m position 44% reduction in Track Data bit traffic at 100m position

threshold and 10m/sec velocity thresholdthreshold and 10m/sec velocity threshold

# # 2121

CEC Message Stream AnalysisCEC Message Stream AnalysisConclusionsConclusions

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

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

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

# # 2222

OutlineOutline






# # 2323

Rich Semantic Track ModelRich Semantic Track Model

Need practical ontologies for important domainsNeed practical ontologies for important domains

TracksTracks are common information elements in are common information elements in numerous military and non-military domainsnumerous military and non-military domains A common “informal” concept in military operationsA common “informal” concept in military operations

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

Semantic hub + translator generators => information Semantic hub + translator generators => information sharingsharing

Provides vocabulary for expressing COIsProvides vocabulary for expressing COIs Provides logical constructs for evaluating COIsProvides logical constructs for evaluating COIs

# # 2424

Rich Semantic Track (RST) Rich Semantic Track (RST)

Rich Semantic Track- conceptual hub for

interchange and automatedreasoning

CECTrack

Messages

JointTrack

ManagementData Model

CMAMaritime

Information Exchange Model

OtherTrack

Data Models

# # 2525

The Rich Semantic The Rich Semantic Track ModelTrack Model

TrackTrackBeliefsBeliefs

Identity and CharacteristicsIdentity and CharacteristicsDynamic State at Time TDynamic State at Time THistory of states (past “track”)History of states (past “track”)Predicted states (future “track”)Predicted states (future “track”)

Meta-Information (applicable to each element of belief)Meta-Information (applicable to each element of belief)Evidence Evidence InferencesInferencesError and uncertainty estimatesError and uncertainty estimatesTemporal qualificationsTemporal qualificationsSpatial qualificationsSpatial qualifications

The top-level conceptual hierarchy for Track.The full hierarchy has more than 125 high level concepts.

# # 2626

CEC/VIRT ProjectCEC/VIRT Project

Investigated mapping of CEC track data to Investigated mapping of CEC track data to RST conceptual modelRST conceptual model

Constructed various RST representations Constructed various RST representations for software and web-based for software and web-based implementationsimplementations Formal logic representation for automating Formal logic representation for automating

mappings across track data modelsmappings across track data models Semantic Web representations for web-based Semantic Web representations for web-based

data interchange and machine reasoningdata interchange and machine reasoning Constructed various web-based expressions Constructed various web-based expressions

of COIsof COIs

# # 2727

Rich Semantic Track:Rich Semantic Track:Influences on Community DevelopmentsInfluences on Community Developments

Defines core semantic model for Defines core semantic model for TrackTrack information combining Beliefs and Meta-information combining Beliefs and Meta-Information on precision and certaintyInformation on precision and certainty Basis for vocabulary of VIRT Conditions of Basis for vocabulary of VIRT Conditions of

InterestInterest Basis for interchange across multiple track data Basis for interchange across multiple track data

models models Basis for formal logic for track computationBasis for formal logic for track computation

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

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

# # 2828

MIEM ObjectivesMIEM ObjectivesShare actionable maritime intelligence Share actionable maritime intelligence

in a net-centric way:in a net-centric way:Simple/raw data exchangeSimple/raw data exchangeFusion output representationFusion output representationAdvanced analytics supportAdvanced analytics support

Establish unambiguous maritime Establish unambiguous maritime lexicon that:lexicon that:

Supports communication among data Supports communication among data providers and consumersproviders and consumers

Embodies broad expertise covering the Embodies broad expertise covering the extent of the maritime domainextent of the maritime domain

Leverages existing models and Leverages existing models and knowledge basesknowledge bases

Enable communications from/with Enable communications from/with future services and capabilitiesfuture services and capabilities

Permit extension to more sophisticated Permit extension to more sophisticated data without change to existing data without change to existing systemssystems

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

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

Inexact Inexact information (“roughly 30 information (“roughly 30 feet long”)feet long”)

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

ConditionalsConditionals (“all facilities open (“all facilities open on Thursdays”)on Thursdays”)

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

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

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

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

# # 2929

Levels of Value Added InformationLevels of Value Added InformationLevelLevel Information TypeInformation Type ExampleExample Value addedValue added

9 9 (highest)(highest)

Case files for key Case files for key entitiesentities

Histories, highlights, Histories, highlights, comprehensive detailscomprehensive details

Enables in-depth Enables in-depth predictive analysispredictive analysis

88 Threats & anomaliesThreats & anomalies Dangerous undeclared Dangerous undeclared cargocargo

Increased pre-Increased pre-emptive threat emptive threat reductionreduction

77 ““Of interest” Of interest” conditions & watch conditions & watch listslists

Suspicious cargo on Suspicious cargo on boardboard

Increased analytical Increased analytical efficiencyefficiency

66 History, behavior & History, behavior & future projectionsfuture projections

Voyages & predicted Voyages & predicted coursescourses

Enables basic Enables basic predictive analysispredictive analysis

55 Multiple alternatives & Multiple alternatives & analysisanalysis

Ambiguity, uncertaintyAmbiguity, uncertainty Direct evidence of Direct evidence of certaintycertainty

44 Degree of belief & Degree of belief & pedigreepedigree

Evidence, qualityEvidence, quality Direct information Direct information about qualityabout quality

33 Fused data & inferred Fused data & inferred beliefsbeliefs

Position, crewPosition, crew Synergistic Synergistic improvement in SAimprovement in SA

22 Caveats & simple Caveats & simple meta-datameta-data

Sensor type, Sensor type, classificationclassification

Indirect quality Indirect quality assessmentassessment

1 1 (lowest)(lowest)

Sensor system Sensor system reportsreports

AISAIS Reduced Reduced development costs development costs for consumersfor consumers

# # 3030

Principal Elements of MIEMPrincipal Elements of MIEM Key Domain EntitiesKey Domain Entities

Conveyance/VesselConveyance/Vessel Person/Crew/PassengerPerson/Crew/Passenger Cargo & FacilitiesCargo & Facilities Measurements: Time, Position, Length, Weight, …Measurements: Time, Position, Length, Weight, …

Key Secondary ConceptsKey Secondary Concepts Life-cycle: States, Transitions, Voyages, EpochsLife-cycle: States, Transitions, Voyages, Epochs Of-interest Of-interest Event Event Anomalies & ThreatsAnomalies & Threats

Extensive & Universally Applicable Meta-dataExtensive & Universally Applicable Meta-data Source, Confidence, Alternatives, Pedigree, Caveats, …Source, Confidence, Alternatives, Pedigree, Caveats, … Past, Present & FuturePast, Present & Future

Universal Extensibility & RestrictionUniversal Extensibility & Restriction All classes can be augmented or simplifiedAll classes can be augmented or simplified

Conceptual model in modular XML schemasConceptual model in modular XML schemas

# # 3131

File & Type Hierarchy of MIEMFile & Type Hierarchy of MIEM

# # 3232

Basis for Further Research, Basis for Further Research, Development and ExperimentationDevelopment and Experimentation

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

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

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

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

# # 3333

OutlineOutline






# # 3434

Semantic Modeling Semantic Modeling and Condition Monitoringand Condition Monitoring

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

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

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

# # 3535

Condition Monitoring is KeyCondition Monitoring is Key

Conditions of Interest (COIs) Conditions of Interest (COIs) Computable expressions (“continuous queries”)Computable expressions (“continuous queries”) Describe critical assumptions (like CCIRs)Describe critical assumptions (like CCIRs) Depend on operator’s evolving contextDepend on operator’s evolving context

Usually reflects phase of a mission & current statusUsually reflects phase of a mission & current status

High-value events are detectedHigh-value events are detected Data describing the event match the COIData describing the event match the COI The event is “news”The event is “news” The COI assures the event is still “relevant”The COI assures the event is still “relevant” Bits reporting the event flow with priorityBits reporting the event flow with priority

Low-value data does not flowLow-value data does not flow Generally relevant data not matching a COIGenerally relevant data not matching a COI Repeated and redundant data, not newsworthyRepeated and redundant data, not newsworthy

# # 3636

OutlineOutline






# # 3737

Opportunities for Further Collaboration (1)Opportunities for Further Collaboration (1)

Recommended next steps for CEC & IWSRecommended next steps for CEC & IWS Develop and implement VIRT principles inside the Develop and implement VIRT principles inside the

CEC network and SIAP (e.g., variable length CEC network and SIAP (e.g., variable length messages sending only message fields that have messages sending only message fields that have significantly changed value)significantly changed value)

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

Spearhead development of rich track model for Spearhead development of rich track model for SIAPSIAP

Develop enhanced toolkit for and methods for Develop enhanced toolkit for and methods for using a rich semantic track modelusing a rich semantic track model Semantic V&VSemantic V&V Interface & service code generatorsInterface & service code generators Track storage & query using XMLTrack storage & query using XML COI specification, event computing, and AAR learningCOI specification, event computing, and AAR learning

# # 3838


Recommendation for JTM Enterprise Recommendation for JTM Enterprise Architecture Working GroupArchitecture Working Group Examine MIEM products of the CMA JCTDExamine MIEM products of the CMA JCTD Identify common concepts and model Identify common concepts and model

componentscomponents Collaborate in developing interchange Collaborate in developing interchange

mechanisms for passing data between the mechanisms for passing data between the modelsmodels

# # 3939


Requested Funding for NPSRequested Funding for NPS Extend formalization of RST for further Extend formalization of RST for further

experimentationexperimentation COI expressionsCOI expressions Computing with uncertaintyComputing with uncertainty Intermediary for automated exchange of data Intermediary for automated exchange of data

across multiple track representations (MIEM, across multiple track representations (MIEM, JTM, others)JTM, others)

Research automated derivation of COIs Research automated derivation of COIs from plans and ordersfrom plans and orders

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

# # 4040

ConclusionConclusion New problems & opportunities combine to change our New problems & opportunities combine to change our

concept of “collaborative communication networks”concept of “collaborative communication networks” Humans must use computers to reduce information glutHumans must use computers to reduce information glut Collaborators need to employ common models to share Collaborators need to employ common models to share

model statemodel state Operators and domain practitioners will use semantic Operators and domain practitioners will use semantic

technologies to create and evolve the needed modelstechnologies to create and evolve the needed models Each consumer’s plans and beliefs determine the value Each consumer’s plans and beliefs determine the value

of informationof information Computers can implement knowledge of decision-Computers can implement knowledge of decision-

makers and current state to determine the flow of bits makers and current state to determine the flow of bits Significant increases in productivity will resultSignificant increases in productivity will result

project report on cec collaboration rick hayes-roth hayes-roth@nps june 15, 2007

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