Semantic Web and Valued Information at the Right Time

(VIRT)

Curtis BlaisResearch Associate

MOVES InstituteNaval Postgraduate School

clblais@nps.edu

RichSemantic

Track

Semantic Interoperability

Joint C3 InformationExchange

Data Model

TacticalAssessment

MarkupLanguage

USW-XML

MIP

MobilityCOP

C-BML

AutonomousVehicle Command

Language

SavageModeling and

AnalysisLanguage

AT/FP

AVCL/AUVW

FCS

GIG

Plansand

Orders

JBML

VIRT

Research Agenda

C2 Ontology-Concepts-Relationships-Rules/Constraints

CEC

JTM

CMA

Semantic Web“An extension of the current Web in which

information is given well-defined meaning, better enabling computers and people to work in

cooperation.” – Berners-Lee, et. al., 2001

• Transforming documents to information (data in context)• Enabling automated reasoning• Equally accessible to human and software agents

The Evolving WebWeb of

Knowledge

HTML/HTTP

Resource Description FrameworkExtensible Markup Language

Self-Describing Documents

Foundation of the Current Web

Proof, Logic andOntology Languages

Shared terminologyMachine-Machine Communication

1990

2000

2010

J. Hendler presentation, W3C , 2001

Explicit semantics through standard languages

Semantic Web Stack

Source: I. Herman: “Introduction to the Semantic Web,” 12 November 2003. http://www.w3.org/2003/Talks/0624-BrusselsSW-IH/26.html

C2 Ontology

Too large to be built all at onceWould take too longWould be too hard to gain widespread acceptance

Evolutionary development Start small (e.g., tracks) Show community how it is done (methodology) Demonstrate benefits (and limitations) Create mechanisms for extensionDissertation: Ontological Foundation for Obtaining Valued Information

at the Right Time in Semantically Rich Network-Centric Architectures

Topics

Applying Semantic Web Technologies to the Tactical Assessment Markup Language (TAML) – ENS Candace Childers CS Thesis, June 2006Sponsor: DoN Chief Information Officer, USW-XML Working Group

Rich Semantic Track and Valued Information at the Right Time – Rick Hayes-Roth, NPS Information SystemsSponsor: NAVSEA PEO IWS6(CEC)

Technology Goal• Demonstrate application of existing and

emerging Semantic Web standards to Network-Centric Architecture

• Explore benefits and limitations of Semantic Web technologies

• Examples:• Conceptual querying across multiple

representations• Combining multiple source data and

drawing inferences across the data

From Feasibility to Practice

• ENS Childers thesis demonstrated feasibility and breadth of application of Semantic Web standards• Tool-based demonstration (Protégé, Twinkle)• Single representation of contacts (TAML)• Single domain (USW)• Static ontology

• Unified Application (Blais dissertation)• Formalized abstraction of Track concept for general

software implementation• Mediation of multiple track representations across

multiple domains• Operator and problem-driven evolution of the ontology

Rich Semantic Track

• Abstract model of battlespace perceptions

• Logical theory enabling reasoning over collected data

• Common semantics underlying multiple systems and across multiple domains• Global Command and Control System, Maritime

Domain Awareness, Cooperative Engagement Capability, TAML, Joint Track Management, etc.

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

Rich Semantic TrackTrack

• 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

*Hayes-Roth. Towards a rich semanticmodel of Track: Essential Foundation forInformation Sharing. NPS Research Paper.Monterey, CA. February 25, 2005.

Technologies to provide Valued Information at the Right Time

Screens and marshals the “data storm”Assists in the filtering of information to

provide guidance based on situational priorities

Automatically adapts to the environment by inferring valued information

• Especially via modeling spatiotemporal “tracks”

• Other class models useful, too

Personalizes, using context, role, and state

What is VIRT?

The Basic Ideas

Synchronize groups by having them operate on semantically aligned and high-value information

Determine what concepts operators’ missions depend on and make those standard

Notice what beliefs underlie mission plans and Courses of Action (COAs)

Automatically inform operators when changes in data affect their beliefs and planning rationales

COIs

Overall Vision: Model-based Communication Networks, VIRT

and Rich Semantic Track

Past

GlobalInformation

Grid

PastPresent

Future

PresentFuture Present

Past

Present

Future

Past

Future

COIs

Shared World Models

Shared World ModelsCommon Track SemanticsState-full Network

COI = Condition of Interest

Overall Vision: Model-based Communication Networks, VIRT

and Rich Semantic Track

Past

PastPresent

Future

PresentFuture Present

Past

Present

Future

Past

Future

Shared World ModelsCommon Track SemanticsState-full Network

Valued Bits

Value

d Bits

GlobalInformation

Grid

Model-based Communication Network (MCN)

Instead of Stateless Networking, State-full• Maintain shared state among collaborators• State = current values of models, e.g.

• The route plan, position, velocity of an aircraft• The current and future position and behavior of a unit• The hypothesized position, status and intention of a system

A shared world model is the goal• Collectively, what the collaborators believe• Distributed, replicated for efficiency• Autonomously updated, through dead-reckoning

Like a distributed blackboard of hypotheses• Re-conceptualize Common Operational Picture• Obviate “communication” of non-news• Emphasize “information,” especially valuable information

Semantic Modeling 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

CEC/VIRT Project

• 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

CEC/VIRT Conditions of Interest

• 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

CEP-to-Track User Messages*

Number of Messages Number of Bits

Without VIRT

With VIRT**

Without VIRT

With VIRT**

Valued Bit Ratio

Track Data 1,852 141 2,483,712

189,504 0.076

Track ID 18 6 9,216 3,072 0.333

Track IFF 121 0 42,592 0 0.000

Cooperating Unit

552 0 176,640 0 0.000

Engagement Status

0 0 0 0 N/A

Status 0 0 0 0 N/A

Time 0 0 0 0 N/A

Totals 2,543 147 2,712,160

192,576 0.071

* 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!

CEC/VIRT Simulation Event Graph

Embedding a semantically rich knowledge base into a simulation framework for testing/experimentation with VIRT/RST concepts in a dynamic context

Embedding a semantically rich knowledge base into a simulation framework for testing/experimentation with VIRT/RST concepts in a dynamic context

Common Implementation Pattern

Contacts

Curtis Blaisclblais@nps.edu

MOVES Institute, Naval Postgraduate SchoolMonterey California 93943-5000 USA

1.831.656.3215 voice1.831.656.7599 fax