Agenda

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

Overview 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)

DAML 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

Task List Ontology

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

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

EOD 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)

Fugitive / 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

Light Weight Reusable Ontologies

Locator

Point of contact

Versioning Element Set (VES)

Dublin Core (DC)

Person

Bibliographic information

Thesaurus – ANSI NISO Z39.19

Military 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

Lessons 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”)

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.

DRC’s Upcoming Work

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)

Deliverables

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)

Metrics

Developed 26 ontologies

Developed 26+ artifacts

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

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

Questions?

BACKUP MATERIALS

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.

The 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

Publishing 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.

Event 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

Military Land Platform Ontology

Ontology focused on a taxonomy of equipment types

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

Slide 22

Foreign 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

Equipment 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

DAML 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


	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


	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)


	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


	Supports representation of military task lists (e.g., UJTL, NTL, AUTL)
	Populating sample instance file with Universal Joint Task List (UJTL)


	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)


	Based on FBI website information
	Potential applications for “watch list” matching
	Description properties include:
		Place of birth
		FBI caution
		Physical description
		Languages used


	Locator
	Point of contact
	Versioning Element Set (VES)
	Dublin Core (DC)
	Person
	Bibliographic information
	Thesaurus – ANSI NISO Z39.19


	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


	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”)


	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.


	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)


	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)


	Developed 26 ontologies
	Developed 26+ artifacts
	Supported 4 military customers (NWDC, CALL, EOD, AMC)
	Transitioning 2 programs to other funding sources (EOD, FCG)


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


	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.


	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



	Ontology focused on a taxonomy of equipment types
	Ontology is modeled after Distributed Interactive Simulation (DIS) Entity Enumerations document


	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


	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


	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