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DAML PI Meeting Status BriefingDAML PI Meeting Status Briefing

Dynamics Research Corporation

Marti Hall

Lee Lacy

February 12-14, 2002

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AgendaAgenda

Overview of DRC’s DAML Work DAML Military Ontologies

Light Weight Reusable Ontologies

Military Knowledge Representation Methodology

Lessons Learned

Quality Assurance Process (Mist)

DRC’s Upcoming Work

Deliverables

Metrics

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Overview of DRC’s DAML WorkOverview of DRC’s DAML Work

Focused on Military Applications

Developed Methodology to Solve Complex Military Problems by Building Ontologies/Artifacts from Light Weight (Primitive/Basic) Ontologies

Developed Methodology for Our Quality Assurance Process for Ontologies and Artifacts

Investigated utility of DAML to provide information to the explosive ordnance disposal (EOD) specialist

Investigated utility of DAML to solve USAF Air Mobility Command problem (Foreign Clearance Guide)

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DAML Military OntologiesDAML Military Ontologies

Task list

Explosive Ordnance Disposal (EOD) scenario/vignette

Event chronology

Fugitive/terrorist description

Military land platform taxonomy

Commercial shipping

Hazardous materials

Foreign Clearance Guide

Equipment Characteristics and Performance (C&P)

IMO intelligence report

FBI Most Wanted Terrorist

Center for Army Lessons Learned Thesaurus

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Task List OntologyTask List Ontology

Supports representation of military task lists (e.g., UJTL, NTL, AUTL)

Populating sample instance file with Universal Joint Task List (UJTL)

OPERATIONALAccomplish Objectives ofAccomplish Objectives of Subordinate Campaigns and Major OperationsSubordinate Campaigns and Major Operations

STRATEGIC NATIONALAccomplish Objectives ofAccomplish Objectives of National Military StrategyNational Military Strategy

OP 1CONDUCT

OPERATIONALMOVEMENT & MANEUVER

OP 2 DEVELOP OPERATIONAL

INTELLIGENCE, SURVEILLANCE, AND RECONNAISSANCE

OP 3EMPLOY

OPERATIONALFIREPOWER

OP 4PROVIDE

OPERATIONALSUPPORT

OP 5EXERCISE

OPERATIONALCOMMAND & CONTROL

OP 6PROVIDE

OPERATIONALPROTECTION

SN 1 CONDUCT STRATEGIC

DEPLOYMENT &REDEPLOYMENT

SN 2 DEVELOP STRATEGIC INTELLIGENCE,

SURVEILLANCE,AND RECONNAISSANCE

SN 3EMPLOYFORCES

SN 4PROVIDE

SUSTAINMENT

SN 5 PROVIDESTRATEGIC DIRECTION

& INTEGRATION

SN 6CONDUCT

MOBILIZATION

SN 7CONDUCT

FORCEDEVELOPMENT

TA 1DEPLOY/CONDUCT

MANEUVER

TA 2DEVELOP

INTELLIGENCE

TA 3EMPLOY

FIREPOWER

TA 4PERFORM LOGISTICS AND

COMBAT SERVICE SUPPORT

TA 5EXERCISE COMMAND

& CONTROL

TA 6PROTECT THE

FORCE

ST 5 PROVIDE THEATER

STRATEGIC COMMAND

AND CONTROL

ST 6PROVIDE THEATERPROTECTION

ST 7 ESTABLISH THEATER

FORCE REQUIREMENTS AND READINESS

ST 8 DEVELOP AND MAINTAIN

ALLIANCEAND REGIONAL

RELATIONS

ST 1 DEPLOY, CONCENTRATE,AND MANEUVER

THEATER FORCES

ST 2 DEVELOP THEATER STRATEGIC

INTELLIGENCE, SURVEILLANCE, AND

RECONNAISSANCE

ST 3EMPLOY THEATER

STRATEGICFIREPOWER

ST 4SUSTAINTHEATER FORCES

STRATEGIC THEATERAccomplish Objectives ofAccomplish Objectives of Theater and Campaign StrategyTheater and Campaign Strategy

TACTICALAccomplish Objectives ofAccomplish Objectives of Battles and EngagementsBattles and Engagements

SN 8 FOSTERMULTINATIONAL

AND INTERAGENCY RELATIONS

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EOD Scenario/VignetteEOD Scenario/Vignette

Developed specific task list for scenario of providing EOD support to clear mines from Straits of Hormuz and open lanes from Saudi Arabia to the oilfields

References tasks from UJTL instance file (shown on previous slide)

Potential applications include support for doctrine development, training, and operations (e.g., Joint EOD Mission Support Center and Decision Support Tools)

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Fugitive / Terrorist Description OntologyFugitive / Terrorist Description Ontology

Based on FBI website information

Potential applications for “watch list” matching

Description properties include: Place of birth

FBI caution

Physical description

Languages used

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Light Weight Reusable OntologiesLight Weight Reusable Ontologies

Locator

Point of contact

Versioning Element Set (VES)

Dublin Core (DC)

Person

Bibliographic information

Thesaurus – ANSI NISO Z39.19

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Military Knowledge Representation MethodologyMilitary Knowledge Representation Methodology

Solving complex military problems requires knowledge representations of tasks, conditions, behaviors, units, and equipment

Our knowledge representation methodology: Develop a limited but realistic scenario

Build up knowledge representations by combining lightweight, reusable, inter-connectable ontologies (e.g., bibliographic references, military equipment)

Develop sample instance data

Develop prototypes of applications that employ the representations

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Lessons LearnedLessons Learned

Common repository of instance data (artifacts) needed.

Problems with sites changing content without changing version number and problems with sites changing URIs or dropping out of existence.

Improved tools such as mark-up tools, ontology development tools, validation, complete set of test cases

Problems representing procedural concepts

Needed quality assurance process for test environment (answered it with a methodology we call, “The Mist”)

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Quality Assurance Process (Mist)Quality Assurance Process (Mist)

The Mist is an implementation of a quality assurance methodology.

It consists of a testing environment for newly developed or new versions of both ontologies and artifacts.

It was developed to take advantage of the DAML Validator and the RDF Validator web-based tools.

The solution is a testing directory on DRC DAML website in which Ontologists have read/write privileges. The directory was dubbed the “Mist.”

The Mist also serves as the inbox for publish-ready ontologies and artifacts.

The Mist preserves the integrity of published DAML files, while empowering Ontologists to validate new/revised DAML files via web-based tools.

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Continue EOD Work Support Joint EOD technology demonstration by providing

ontologies, DAML artifacts

Support IPT meetings

Participate in the DAML Experiment Provide linkage from Afghanistan scenario to UJTL

Represent the national goals and objectives

Provide various supporting ontologies (e.g., weather ontology)

DRC’s Upcoming WorkDRC’s Upcoming Work

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DeliverablesDeliverables

EOD Requirements analysis documents for EOD knowledge representation

for EOD DSS (Word document)

Data model diagrams (IDEF1X or UML tool files)

DAML ontologies and sample artifacts (DAML files)

DAML Experiment Artifact tying Afghanistan scenario back to UJTL (DAML file)

Related ontologies, e.g., weather ontology and UJTL conditions (DAML files)

Artifact representing the national goals and objectives (DAML files)

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MetricsMetrics

Developed 26 ontologies

Developed 26+ artifacts

Supported 4 military customers (NWDC, CALL, EOD, AMC)

Transitioning 2 programs to other funding sources (EOD, FCG)

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Questions?Questions?

http://orlando.drc.com/DAML/

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BACKUP MATERIALSBACKUP MATERIALS

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What is the Mist?What is the Mist?

The Mist is an implementation of a quality assurance methodology.

It consists of a testing environment for newly developed or new versions of both ontologies and artifacts.

It was developed to take advantage of the DAML Validator and the RDF Validator web-based tools. The web tools require the file under test to have a valid URL.

However, for a variety of reasons, a webmaster should be the only one allowed make changes to website content.

While under test, a DAML file is likely to change too frequently to be officially published by a webmaster.

This conflict created a need for a location wherein an Ontologist can “publish” developing DAML files for testing purposes.

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The Mist SolutionThe Mist Solution

The solution is a testing directory on DRC DAML website in which Ontologists have read/write privileges. The directory was dubbed the “Mist.” One constraint on use of the Mist is that the resulting URI for a DAML

file under test, must be virtually identical to the URI it should have once officially published.

Thus the only difference between the a Mist URI and an officially published URI is the inclusion of the .../mist/… directory, i.e.:

http://orlando.drc.com/daml/ontology/Locator/G3/Locator-ont-g3r1.daml

http://orlando.drc.com/daml/mist/ontology/Locator/G3/Locator-ont-g3r1.daml

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Publishing from the MistPublishing from the Mist

The Mist also serves as the inbox for publish-ready ontologies and artifacts. The Ontologist simply needs to inform the Webmaster that a

particular DAML file in the Mist is ready for publication.

The Webmaster can then remove references to the Mist directory from the validated DAML file and move it to its official location.

The Mist preserves the integrity of published DAML files, while empowering Ontologists to validate new/revised DAML files via web-based tools.

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Event Chronology OntologyEvent Chronology Ontology

Potential application for intelligence report representation (event-centric)

Populated sample file with events from 9/11 based on CNN chronology

Populated another sample with FBI chronology of Atta activities prior to attacks

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Military Land Platform OntologyMilitary Land Platform Ontology

Ontology focused on a taxonomy of equipment types

Ontology is modeled after Distributed Interactive Simulation (DIS) Entity Enumerations document

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Ontology Development

Commercial Shipping OntologyCommercial Shipping Ontology

• Define Commercial Ship• Classes• Subclasses• Attributes• Instance Data

“Authoritative” Data Source

Data Analysis &

Decomposition

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Foreign Clearance GuideForeign Clearance Guide

AFRL conducting research to reduce cost and time required to obtain clearances from foreign governments

Focused on lead times associated with diplomatic (DIP) clearances

Migrated IDEF1X data model to DAML+OIL ontology

Knowledge acquisition at Scott AFB in joint project with BBN

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Equipment Characteristics and PerformanceEquipment Characteristics and Performance

Equipment descriptions used by simulation applications for accurately representing platforms

Leveraged DRC work for Army Modeling and Simulation Office (AMSO)

Sample artifact developed based on Universal Threat System for Simulators (UTSS) sample data for AH-64A

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DAML Development for UTSS ExperimentDAML Development for UTSS Experiment

Created an Entity DAML ontology with Platform and Munitions (based on DIS Entity Enumeration taxonomy)

Created UTSS-specific DAML ontology tied to Platform ontology (i.e., A64A subclass of A64A class)

Translated UTSS data into DAML artifact / instance file