applying semantic rules for dynamic service-oriented...

©© 2006 The MITRE Corporation. All rights reserved2006 The MITRE Corporation. All rights reserved10 November 200610 November 2006

Applying Semantic Rulesfor Dynamic

Service-Oriented Architecture

Applying Semantic RulesApplying Semantic Rulesfor Dynamic for Dynamic

ServiceService --Oriented ArchitectureOriented Architecture

Suzette Stoutenburg, Leo Obrst, Suzette Stoutenburg, Leo Obrst,

Deborah NicholsDeborah Nichols, Ken Samuel, and Paul Franklin, Ken Samuel, and Paul Franklin

22 ©© 2006 The MITRE Corporation. All rights reserved2006 The MITRE Corporation. All rights reserved10 November 200610 November 2006

Rules and Application Development

Research Team MembersResearch Team Members

Suzette StoutenburgE540/Colo Spgs

Leo Obrst, Ph.D.E544/McLean

Principal Investigators

Ontology and Logic Environment

Karen FoxE540/Colo Spgs

Deborah NicholsE544/McLean

Paul FranklinE540/Colo Spgs

Ken Samuel, Ph.D.E544/McLean


ObjectivesObjectives

Identify sponsorIdentify sponsor--specific requirements for semantic specific requirements for semantic rules and ensure that they are captured in the rules and ensure that they are captured in the emerging World Wide Web Consortium (emerging World Wide Web Consortium (W3CW3C) ) recommendation recommendation �� Rules separated from executable codeRules separated from executable code�� Rules integrated with ontologies to leverage logicRules integrated with ontologies to leverage logic

Demonstrate a Demonstrate a dynamicdynamic ServiceService--Oriented Oriented Architecture using rules that allow adaptive change Architecture using rules that allow adaptive change in standard operating proceduresin standard operating procedures�� Rules supporting situation awareness Rules supporting situation awareness �� Rules adjusting in response to realRules adjusting in response to real--time eventstime events

Optimization of the Logic Programming Optimization of the Logic Programming environment that integrates and reasons over environment that integrates and reasons over rules and ontologiesrules and ontologies


Mission Use Case Key ConceptsMission Use Case Key Concepts

Convoy

Region of interest (ROI) provides“safety zone” around convoy

Unknown GMTI

Hostile GMTI

Intel Summary and ROI

Friendly GMTI

Path of UAVROI around unknown

GMTI

Convoy route

UAV

A track is said to be the “focal object” of an ROI


Scenario Ontology OverviewScenario Ontology Overview

TheaterObject

hasFocalObject

DynamicRegionofInterestMilitaryUnit DynamicRegionofInterestMilitaryUnit

subclassOf

subclassOf

RegionOfInterest

subclassOf

Convoy ConvoyRouteConvoy ConvoyRoute

hasCurrentRoute

ConditionsAndAlerts

conditionAffects

describedBy

ObservationArtifact

GMTIObservation

IntelSummary

VMTIObservation

subclassOf

Primary Ontology

Major classwithin ontology


Applications of RulesApplications of Rules

Support intelligent processing of realSupport intelligent processing of real--time eventstime events�� Synthesize information from multiple sourcesSynthesize information from multiple sources�� Apply data integrity constraintsApply data integrity constraints�� (Future work) Mediate between conflicting sources, and(Future work) Mediate between conflicting sources, and�� Derive new knowledge based on source type and reliabilityDerive new knowledge based on source type and reliability

Construct conceptualization of the battlespace for Construct conceptualization of the battlespace for enhanced situational awarenessenhanced situational awareness�� Transfer attribute values from ObservationArtifacts to Transfer attribute values from ObservationArtifacts to

TheaterObjectsTheaterObjects�� Establish Establish ‘‘safety zonessafety zones’’ and and ‘‘threat areasthreat areas’’ ((ROIsROIs) for objects) for objects�� Detect and report threats to friendly forcesDetect and report threats to friendly forces

Assist decision makers in applying Rules of Assist decision makers in applying Rules of Engagement to developing situationsEngagement to developing situations


Year 2 Prototype ModificationsYear 2 Prototype Modifications

Modifications to the ontologiesModifications to the ontologies�� Added properties to support new rules and represent additional Added properties to support new rules and represent additional

information from messagesinformation from messages�� Added subclasses of weapons and vehicles Added subclasses of weapons and vehicles �� Classes and relations for other domains (missile, maritime, airsClasses and relations for other domains (missile, maritime, airspace)pace)

Rules made more robustRules made more robust�� Detect when new TheaterObjects should be createdDetect when new TheaterObjects should be created�� Some geospatial rules to detect enemy approaching, overtaking, eSome geospatial rules to detect enemy approaching, overtaking, etc. tc. �� Added Added ““extensionsextensions”” to SWRL, by creating predicates to:to SWRL, by creating predicates to:

Create new instancesCreate new instancesApply message data to the set of instancesApply message data to the set of instancesSupport nonSupport non--monotonic reasoningmonotonic reasoning

Dynamic rule changes supported in a Dynamic rule changes supported in a SOASOA with with communications across Enterprise Service Bus (ESB)communications across Enterprise Service Bus (ESB)


Rules for Dynamic ServicesRules for Dynamic Services

Rule Set 1

Situation Awareness

Service

Rule Set 2

Goal: Dynamic service behavior based on realGoal: Dynamic service behavior based on real --time events time events

Create a generic service, e.g., Create a generic service, e.g., ““ What are the What are the implications of information updates for implications of information updates for

convoy security?convoy security? ””

Abstract from service behavior and Abstract from service behavior and express in the form of rulesexpress in the form of rules

If good visibility, send If good visibility, send out out UAVUAV to take closer to take closer

look at unknown look at unknown movermover

If poor visibility, If poor visibility, avoid encounters avoid encounters

with unknown moverswith unknown movers

Applicable Rule Set produces Applicable Rule Set produces appropriate response:appropriate response:

In normal daytime conditions, Rule Set 1 In normal daytime conditions, Rule Set 1 is in effectis in effect

RealReal--time weather event causes Rule time weather event causes Rule Set 2 to take effectSet 2 to take effect


Sample Rules (Day)Sample Rules (Day)

an unknown mover is within the convoy’s ‘safety zone’alert the commander that there is a nearby unknown mover

IFTHEN

an unknown mover is within the convoy’s ‘safety zone’recommend that the convoy deploy UAV reconnaissance

IFTHEN


Sample Rules (Night)Sample Rules (Night)

an unknown mover is within the convoy’s ‘safety zone’alert the commander that there is a nearby unknown mover

IFTHEN

[above] & the convoy has a viable alternate route recommend that the convoy change to the route

IFTHEN


Logic Programming EnvironmentLogic Programming Environment

Developed Developed SWORIERSWORIER (Semantic Web Ontologies & Rules for (Semantic Web Ontologies & Rules for Interoperability with Efficient Reasoning) Interoperability with Efficient Reasoning) �� Reasons over ontologies and rules and answers queries with LogicReasons over ontologies and rules and answers queries with Logic

ProgrammingProgramming

Designed general Prolog predicates to implement the semantics Designed general Prolog predicates to implement the semantics of OWL (e.g., of OWL (e.g., hasPropertyWithhasPropertyWith, , disjointClassesdisjointClasses, , logicNotlogicNot))

Addressed major challengesAddressed major challenges�� Prolog and OWL define negation differentlyProlog and OWL define negation differently

�� Prolog assumes closed world, while OWL assumes open worldProlog assumes closed world, while OWL assumes open world

�� Disjoint and complementary classesDisjoint and complementary classesPrevious work claimed this was not possible [Previous work claimed this was not possible [VolzVolz et al., 2003]et al., 2003]

�� Simpler approach for equivalenceSimpler approach for equivalence

Initial performance of Initial performance of SWORIERSWORIER slow; improvements gained slow; improvements gained with with extensionalizationextensionalization, caching, and code minimization, caching, and code minimization


Logic Programming Logic Programming ChallengesChallenges

Logical NegationLogical NegationOpen/Closed WorldOpen/Closed WorldComplementary/Disjoint Complementary/Disjoint Classes*Classes*Disjunctive Disjunctive Conclusions*Conclusions*Enumerated Classes*Enumerated Classes*Equivalent Individuals*Equivalent Individuals*

* Solutions to be implemented* Solutions to be implemented

Error MessagesError Messages

Existential Existential Quantification*Quantification*

Cardinality Restrictions*Cardinality Restrictions*

Cyclic HierarchiesCyclic Hierarchies

Anonymous ClassesAnonymous Classes

Duplicate FactsDuplicate Facts


Knowledge Base DesignKnowledge Base Design

Translation(XSLT)

Extensionalization

User

Que

ries

An

swers

Changes

ExtensionalProgram(Prolog)

Que

ries

Answ

ers


Dynam

ic

GeneralRules

(Prolog)

IntensionalProgram(Prolog)


Developer

CardinalityRules

(Prolog)

RuleML rulesSWRL

rulesOWLontologies

Translation(XSLT)

Extensionalization

User

Que

ries

An

swers

Changes


Que

ries

Answ

ers


Dynam

ic

GeneralRules

(Prolog)



Developer

CardinalityRules

(Prolog)

RuleML rulesSWRL

rulesOWLontologies

Translation(XSLT)

Translation(XSLT)

Extensionalization

UserUser

Que

ries

An

swers

Changes



Que

ries

Answ

ers


Dynam

ic

GeneralRules

(Prolog)

GeneralRules

(Prolog)






DeveloperDeveloperDeveloper

CardinalityRules

(Prolog)

CardinalityRules

(Prolog)

RuleML rulesSWRL

rulesSWRLrulesOWLontologies

Rules not expressible in SWRL were represented in Pr olog directly; now in the process of specifying extensio ns on SWRL


Design DecisionsDesign Decisions

Enterprise Service Bus (ESB) technology selected Enterprise Service Bus (ESB) technology selected for underlying communication infrastructurefor underlying communication infrastructure�� Supports integration with other applications and prototypes Supports integration with other applications and prototypes

Google Earth used as clientGoogle Earth used as client�� Provides realistic maps and zoomProvides realistic maps and zoom--in capabilitiesin capabilities�� Supports integration with other applicationsSupports integration with other applications

Ground facts for instances stored in the Knowledge Ground facts for instances stored in the Knowledge Base (instead of database) for simplicityBase (instead of database) for simplicitySeparate simulation for Convoy used, making Separate simulation for Convoy used, making Convoy behavior independent of message injectionConvoy behavior independent of message injectionIssue: How should rules be swapped?Issue: How should rules be swapped?�� Since instances are stored in the Knowledge Base, how are they Since instances are stored in the Knowledge Base, how are they

persisted after the rule swap?persisted after the rule swap?�� Decision: Instantiate multiple Knowledge Bases, apply Decision: Instantiate multiple Knowledge Bases, apply

updated instances to eachupdated instances to each


Architecture Options for RulesArchitecture Options for Rules

KnowledgeBase 1

(Ontology, Rules, Instances)

KnowledgeBase 2

(Ontologies, Rules, Instances

Logic Server 1 Logic Server 2

KnowledgeBase1

(Ontology, Rules)

KnowledgeBase2

(Ontologies, Rules)


Database( Instances)

Option 1: Instances in Knowledge BaseInstances must be persisted across multiple KBs

Option 2: Instances in Database layerTools must support links from KB to database

Option 3: PreferredMeta-rules control application to KBinstances in database

KnowledgeBase 1

(Ontology, Rules)

KnowledgeBase2

(Ontologies, Rules)


MetaRules

Database( Instances)


Prototype ArchitecturePrototype Architecture

Events(GMTI, INTSUM)

SituationalAwareness

Service

Enterprise Service Bus

2. Message injection starts

AMZI LogicServer 1

AMZI LogicServer 2

1. Logic Servers instantiated with Rule Sets

3. Adapter performs schema-based transformation of messages

4. New input applied to Knowledge Bases – positions displayed on Client

Google EarthClient

Adapter

6. Sit’n Service detects events on ESB, queries for ale rts

7. Rules fire to produce “Single Integrated Picture ”

8. Alerts and Recommendations based on battlefield movement and Intel are displayed on client

MessageInjector

5. Rules fire to relate messages to Theater Object s

SimulatedPosition of

Friendly Convoy

OptimizedKnowledge

Base 1

OptimizedKnowledge

Base 2


Client DisplayClient Display

RECOMMENDATION: Take alternate routeALERT: Intelligence report of unknown force in vicinity


Summary of FindingsSummary of Findings

OWL is expressive and meets the majority of OWL is expressive and meets the majority of identified DoD requirementsidentified DoD requirementsSWRLSWRL has robust integration with ontologieshas robust integration with ontologiesSWRLSWRL does not fully support the DoD does not fully support the DoD requirements identified in this use caserequirements identified in this use caseTranslation of OWL to executable (Prolog) Translation of OWL to executable (Prolog) environment difficultenvironment difficultTranslation of rule languages fairly Translation of rule languages fairly straightforwardstraightforwardIntegrated framework of tools and capabilities Integrated framework of tools and capabilities needed to support semantic web needed to support semantic web developmentdevelopment


Future WorkFuture Work

Develop Develop metameta--rules to rules to select rule setselect rule setCompletion of Completion of SWORIERSWORIERStorage of Storage of instances in a instances in a databasedatabaseExtend to new Extend to new domainsdomains


Backup SlidesBackup Slides


Year 2 Scenario: Year 2 Scenario: Handling Dynamic EventsHandling Dynamic Events

Convoy moving throughenemy territory

Convoy nears sniperposition, changes route

Unknown GMTI reportedalong route

UAV retasked toinvestigate GMTI

UAV confirms enemyGMTI

Enemy GMTI in proximityConvoy alerted

Convoy moving throughenemy territory

Convoy nears sniperposition, changes route

Unknown GMTI reportedalong route

No need for UAV to investigate; route mustchange regardless, per

new rules of engagement

Convoy changesroute

Convoy CDR reportsunexpected sandstorm

New rules ofengagement applied


Two Dynamic Changes (Online)Apply the location and speed of a convoy

Apply the location and speed of an enemy motorized infantry unit

Desired Time:Baseline:

With Code Minimization:

a few seconds25.2 minutes10 milliseconds

Two Queries (Online)What are the locations and speeds of all known units?

What are all of the alerts and recommendations?


With extensionalization:& Dynamic Changes:& Code Minimization:

a few seconds33 minutes110 milliseconds58 minutes130 milliseconds

Extensionalization (Offline)


With Avoiding Reanalysis:& Code Minimization:

a few hoursCRASH13 hours6.5 hours

SWORIERSWORIER: Efficient Reasoning, : Efficient Reasoning, Dynamic UpdatesDynamic Updates


Project ProductsProject Products

Stoutenburg, Suzette; Leo Obrst; Deborah Nichols; Ken Samuel; KeStoutenburg, Suzette; Leo Obrst; Deborah Nichols; Ken Samuel; Ken Laskey; Adrian Johnson; Jason Peterson; n Laskey; Adrian Johnson; Jason Peterson; Karen Fox. 2006. Karen Fox. 2006. Dynamic Service Oriented Architectures through Semantic TechnoloDynamic Service Oriented Architectures through Semantic Technologygy. Submitted to 4th . Submitted to 4th International Conference on Service Oriented Computing (International Conference on Service Oriented Computing (ICSOCICSOC 2006).2006).Samuel, Ken; Leo Obrst; Suzette Stoutenburg; Deborah Nichols; AdSamuel, Ken; Leo Obrst; Suzette Stoutenburg; Deborah Nichols; Adrian Johnson; Ken Laskey; Jason Peterson; rian Johnson; Ken Laskey; Jason Peterson; Karen Fox. 2006. Karen Fox. 2006. Transforming OWL and Semantic Web Rules to Prolog: Towards DescrTransforming OWL and Semantic Web Rules to Prolog: Towards Description Logic Programsiption Logic Programs. . Federated Logic Conference, August 2006, Seattle, Washington.Federated Logic Conference, August 2006, Seattle, Washington.Stoutenburg, Suzette; Leo Obrst; Deborah Nichols; Ken Samuel; KeStoutenburg, Suzette; Leo Obrst; Deborah Nichols; Ken Samuel; Ken Laskey; Adrian Johnson; Jason Peterson; n Laskey; Adrian Johnson; Jason Peterson; Karen Fox. 2006. Karen Fox. 2006. Toward a Standard Rule Language for Semantic Enterprise IntegratToward a Standard Rule Language for Semantic Enterprise Integration; Year 1 Results: ion; Year 1 Results: Evaluating Proposed Approaches for a Standard Semantic Web Rule Evaluating Proposed Approaches for a Standard Semantic Web Rule LanguageLanguage. MITRE Technical Report, March . MITRE Technical Report, March 2006.2006.Stoutenburg, Suzette; Deborah Nichols. 2005. Stoutenburg, Suzette; Deborah Nichols. 2005. Toward a Standard Rule Language for Semantic Enterprise Toward a Standard Rule Language for Semantic Enterprise IntegrationIntegration. 2005 International Conference on Rules and Rule Markup Langua. 2005 International Conference on Rules and Rule Markup Languages for the Semantic Web, poster, ges for the Semantic Web, poster, RuleML 2005, November 2005, Galway, Ireland.RuleML 2005, November 2005, Galway, Ireland.Stoutenburg, Suzette. Stoutenburg, Suzette. Logics for the Semantic Web (for the nonLogics for the Semantic Web (for the non--logician).logician). MITRE Working Note, January 2006.MITRE Working Note, January 2006.Obrst, Leo; Todd Hughes; Steve Ray. 2006. Obrst, Leo; Todd Hughes; Steve Ray. 2006. Prospects and Possibilities for Ontology Evaluation: The View frProspects and Possibilities for Ontology Evaluation: The View from om NCORNCOR.. Workshop on Evaluation of Ontologies for the Web (Workshop on Evaluation of Ontologies for the Web (EON2006EON2006), Edinburgh, UK, May 22, 2006.), Edinburgh, UK, May 22, 2006.Obrst, Leo; Werner Obrst, Leo; Werner CeustersCeusters; Inderjeet Mani; Steve Ray; Barry Smith. 2006. ; Inderjeet Mani; Steve Ray; Barry Smith. 2006. The Evaluation of Ontologies: The Evaluation of Ontologies: Toward Improved Semantic Interoperability.Toward Improved Semantic Interoperability. Chapter in: Chapter in: Semantic Web: Revolutionizing Knowledge Discovery in Semantic Web: Revolutionizing Knowledge Discovery in the Life Sciences,the Life Sciences, Christopher J. O. Baker and KeiChristopher J. O. Baker and Kei--Hoi Cheung, Eds., Springer, forthcoming 2006.Hoi Cheung, Eds., Springer, forthcoming 2006.Obrst, Leo; Patrick Cassidy; Steve Ray; Barry Smith; Dagobert SoObrst, Leo; Patrick Cassidy; Steve Ray; Barry Smith; Dagobert Soergel; Matthew West; Peter Yim. 2006. The ergel; Matthew West; Peter Yim. 2006. The 2006 Upper Ontology Summit Joint Communiqu2006 Upper Ontology Summit Joint Communiquéé. Journal of Applied Formal Ontology. Forthcoming.. Journal of Applied Formal Ontology. Forthcoming.PoliPoli, Roberto; Leo Obrst. 2006. , Roberto; Leo Obrst. 2006. The Interplay Between Ontology as Categorical Analysis and OntolThe Interplay Between Ontology as Categorical Analysis and Ontology as ogy as TechnologyTechnology.. Chapter 9 in Part One: Ontology as Technology in the book: TAO Chapter 9 in Part One: Ontology as Technology in the book: TAO –– Theory and Applications of Theory and Applications of Ontology, Volume 2: The InformationOntology, Volume 2: The Information--science Stance, Michael Healy, Achilles science Stance, Michael Healy, Achilles KameasKameas, Roberto , Roberto PoliPoli, eds. , eds. Forthcoming.Forthcoming.Obrst, Leo. 2006. Obrst, Leo. 2006. Ontological ArchitecturesOntological Architectures. Chapter 2 in Part One: Ontology as Technology in the book: TAO. Chapter 2 in Part One: Ontology as Technology in the book: TAO ––Theory and Applications of Ontology, Volume 2: The InformationTheory and Applications of Ontology, Volume 2: The Information--science Stance, Michael Healy, Achilles science Stance, Michael Healy, Achilles KameasKameas, Roberto , Roberto PoliPoli, eds. Forthcoming., eds. Forthcoming.

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