DAML PI Meeting Status Briefing

1. DAML PI Meeting Status Briefing Dynamics Research Corporation Marti Hall Lee Lacy February 12-14, 2002

2. 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

3. 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)

4. 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 DAML Military Ontologies

5. Accomplish Objectives of National Military Strategy STRATEGIC NATIONAL SN 8FOSTER MULTINATIONAL AND INTERAGENCY RELATIONS SN 7 CONDUCT FORCE DEVELOPMENT SN 4 PROVIDE SUSTAINMENT SN 2DEVELOP STRATEGIC INTELLIGENCE, SURVEILLANCE, AND RECONNAISSANCE SN 3 EMPLOY FORCES SN 5PROVIDE STRATEGIC DIRECTION & INTEGRATION SN 6 CONDUCT MOBILIZATION SN 1CONDUCT STRATEGIC DEPLOYMENT & REDEPLOYMENT Accomplish Objectives of Theater and Campaign Strategy STRATEGIC THEATER ST 8DEVELOP AND MAINTAIN ALLIANCE AND REGIONAL RELATIONS ST 6 PROVIDE THEATER PROTECTION ST 7ESTABLISH THEATER FORCE REQUIREMENTS AND READINESS ST 5PROVIDE THEATER STRATEGIC COMMAND AND CONTROL ST 1DEPLOY, CONCENTRATE, AND MANEUVER THEATER FORCES ST 2DEVELOP THEATER STRATEGIC INTELLIGENCE, SURVEILLANCE, AND RECONNAISSANCE ST 3 EMPLOY THEATER STRATEGIC FIREPOWER ST 4 SUSTAIN THEATER FORCES Subordinate Campaigns and Major Operations Accomplish Objectives of OPERATIONAL OP 3 EMPLOY OPERATIONAL FIREPOWER OP 2 DEVELOP OPERATIONAL INTELLIGENCE, SURVEILLANCE, AND RECONNAISSANCE OP 4 PROVIDE OPERATIONAL SUPPORT OP 1 CONDUCT OPERATIONAL MOVEMENT & MANEUVER OP 5 EXERCISE OPERATIONAL COMMAND & CONTROL OP 6 PROVIDE OPERATIONAL PROTECTION Battles and Engagements Accomplish Objectives of TACTICAL TA 5 EXERCISE COMMAND & CONTROL TA 6 PROTECT THE FORCE TA 1 DEPLOY/CONDUCT MANEUVER TA 2 DEVELOP INTELLIGENCE TA 3 EMPLOY FIREPOWER TA 4 PERFORM LOGISTICS AND COMBAT SERVICE SUPPORT Task List Ontology • Supports representation of military task lists (e.g., UJTL, NTL, AUTL) • Populating sample instance file with Universal Joint Task List (UJTL)

6. 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)

7. 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

8. Light Weight Reusable Ontologies • Locator • Point of contact • Versioning Element Set (VES) • Dublin Core (DC) • Person • Bibliographic information • Thesaurus – ANSI NISO Z39.19

9. 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

10. 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”)

11. 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.

12. 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)

13. 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)

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

15. Questions? http://orlando.drc.com/DAML/

16. BACKUP MATERIALS

17. 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.

18. 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

19. 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.

20. 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

21. Military Land Platform Ontology • Ontology focused on a taxonomy of equipment types • Ontology is modeled after Distributed Interactive Simulation (DIS) Entity Enumerations document

22. Commercial Shipping Ontology Ontology Development Data Analysis & Decomposition “Authoritative” Data Source • Define Commercial Ship • Classes • Subclasses • Attributes • Instance Data

23. 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

24. 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

25. 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