Presentation on theme: "1 DAML PI Meeting Status Briefing Dynamics Research Corporation Marti Hall Lee Lacy February 12-14, 2002."— Presentation transcript:
1 DAML PI Meeting Status Briefing Dynamics Research Corporation Marti Hall Lee Lacy February 12-14, 2002
2 Agenda n Overview of DRCs DAML Work l DAML Military Ontologies l Light Weight Reusable Ontologies l Military Knowledge Representation Methodology l Lessons Learned l Quality Assurance Process (Mist) n DRCs Upcoming Work n Deliverables n Metrics
3 Overview of DRCs DAML Work n Focused on Military Applications n Developed Methodology to Solve Complex Military Problems by Building Ontologies/Artifacts from Light Weight (Primitive/Basic) Ontologies n Developed Methodology for Our Quality Assurance Process for Ontologies and Artifacts n Investigated utility of DAML to provide information to the explosive ordnance disposal (EOD) specialist n Investigated utility of DAML to solve USAF Air Mobility Command problem (Foreign Clearance Guide)
4 DAML Military Ontologies n Task list n Explosive Ordnance Disposal (EOD) scenario/vignette n Event chronology n Fugitive/terrorist description n Military land platform taxonomy n Commercial shipping n Hazardous materials n Foreign Clearance Guide n Equipment Characteristics and Performance (C&P) n IMO intelligence report n FBI Most Wanted Terrorist n Center for Army Lessons Learned Thesaurus
5 Task List Ontology n Supports representation of military task lists (e.g., UJTL, NTL, AUTL) n Populating sample instance file with Universal Joint Task List (UJTL) OPERATIONAL Accomplish Objectives of Subordinate Campaigns and Major Operations STRATEGIC NATIONAL Accomplish Objectives of National Military Strategy OP 1 CONDUCT OPERATIONAL MOVEMENT & MANEUVER OP 2 DEVELOP OPERATIONAL INTELLIGENCE, SURVEILLANCE, AND RECONNAISSANCE OP 3 EMPLOY OPERATIONAL FIREPOWER OP 4 PROVIDE OPERATIONAL SUPPORT OP 5 EXERCISE OPERATIONAL COMMAND & CONTROL OP 6 PROVIDE OPERATIONAL PROTECTION SN 1 CONDUCT STRATEGIC DEPLOYMENT & REDEPLOYMENT SN 2 DEVELOP STRATEGIC INTELLIGENCE, SURVEILLANCE, AND RECONNAISSANCE SN 3 EMPLOY FORCES SN 4 PROVIDE SUSTAINMENT SN 5 PROVIDE STRATEGIC DIRECTION & INTEGRATION SN 6 CONDUCT MOBILIZATION SN 7 CONDUCT FORCE DEVELOPMENT TA 1 DEPLOY/CONDUCT MANEUVER TA 2 DEVELOP INTELLIGENCE TA 3 EMPLOY FIREPOWER TA 4 PERFORM LOGISTICS AND COMBAT SERVICE SUPPORT TA 5 EXERCISE COMMAND & CONTROL TA 6 PROTECT THE FORCE ST 5 PROVIDE THEATER STRATEGIC COMMAND AND CONTROL ST 6 PROVIDE THEATER PROTECTION ST 7 ESTABLISH THEATER FORCE REQUIREMENTS AND READINESS ST 8 DEVELOP AND MAINTAIN ALLIANCE AND REGIONAL RELATIONS ST 1 DEPLOY, CONCENTRATE, AND MANEUVER THEATER FORCES ST 2 DEVELOP THEATER STRATEGIC INTELLIGENCE, SURVEILLANCE, AND RECONNAISSANCE ST 3 EMPLOY THEATER STRATEGIC FIREPOWER ST 4 SUSTAIN THEATER FORCES STRATEGIC THEATER Accomplish Objectives of Theater and Campaign Strategy TACTICAL Accomplish Objectives of Battles and Engagements SN 8 FOSTER MULTINATIONAL AND INTERAGENCY RELATIONS
6 EOD Scenario/Vignette n 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 n References tasks from UJTL instance file (shown on previous slide) n 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 n Based on FBI website information n Potential applications for watch list matching n Description properties include: l Place of birth l FBI caution l Physical description l Languages used
8 Light Weight Reusable Ontologies n Locator n Point of contact n Versioning Element Set (VES) n Dublin Core (DC) n Person n Bibliographic information n Thesaurus – ANSI NISO Z39.19
9 Military Knowledge Representation Methodology n Solving complex military problems requires knowledge representations of tasks, conditions, behaviors, units, and equipment n Our knowledge representation methodology: l Develop a limited but realistic scenario l Build up knowledge representations by combining lightweight, reusable, inter-connectable ontologies (e.g., bibliographic references, military equipment) l Develop sample instance data l Develop prototypes of applications that employ the representations
10 Lessons Learned n Common repository of instance data (artifacts) needed. n Problems with sites changing content without changing version number and problems with sites changing URIs or dropping out of existence. n Improved tools such as mark-up tools, ontology development tools, validation, complete set of test cases n Problems representing procedural concepts n Needed quality assurance process for test environment (answered it with a methodology we call, The Mist)
11 Quality Assurance Process (Mist) n The Mist is an implementation of a quality assurance methodology. n It consists of a testing environment for newly developed or new versions of both ontologies and artifacts. n It was developed to take advantage of the DAML Validator and the RDF Validator web-based tools. n The solution is a testing directory on DRC DAML website in which Ontologists have read/write privileges. The directory was dubbed the Mist. n The Mist also serves as the inbox for publish-ready ontologies and artifacts. n The Mist preserves the integrity of published DAML files, while empowering Ontologists to validate new/revised DAML files via web-based tools.
12 n Continue EOD Work l Support Joint EOD technology demonstration by providing ontologies, DAML artifacts l Support IPT meetings n Participate in the DAML Experiment l Provide linkage from Afghanistan scenario to UJTL l Represent the national goals and objectives l Provide various supporting ontologies (e.g., weather ontology) DRCs Upcoming Work
13 Deliverables n EOD l Requirements analysis documents for EOD knowledge representation for EOD DSS (Word document) l Data model diagrams (IDEF1X or UML tool files) l DAML ontologies and sample artifacts (DAML files) n DAML Experiment l Artifact tying Afghanistan scenario back to UJTL (DAML file) l Related ontologies, e.g., weather ontology and UJTL conditions (DAML files) l Artifact representing the national goals and objectives (DAML files)
14 Metrics n Developed 26 ontologies n Developed 26+ artifacts n Supported 4 military customers (NWDC, CALL, EOD, AMC) n Transitioning 2 programs to other funding sources (EOD, FCG)
17 What is the Mist? n The Mist is an implementation of a quality assurance methodology. n It consists of a testing environment for newly developed or new versions of both ontologies and artifacts. n It was developed to take advantage of the DAML Validator and the RDF Validator web-based tools. l The web tools require the file under test to have a valid URL. l However, for a variety of reasons, a webmaster should be the only one allowed make changes to website content. l While under test, a DAML file is likely to change too frequently to be officially published by a webmaster. l This conflict created a need for a location wherein an Ontologist can publish developing DAML files for testing purposes.
18 The Mist Solution n The solution is a testing directory on DRC DAML website in which Ontologists have read/write privileges. The directory was dubbed the Mist. l 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. l Thus the only difference between the a Mist URI and an officially published URI is the inclusion of the.../mist/… directory, i.e.: u http://orlando.drc.com/daml/ontology/Locator/G3/Locator-ont-g3r1.daml u http://orlando.drc.com/daml/mist/ontology/Locator/G3/Locator-ont-g3r1.daml
19 Publishing from the Mist n The Mist also serves as the inbox for publish-ready ontologies and artifacts. l The Ontologist simply needs to inform the Webmaster that a particular DAML file in the Mist is ready for publication. l The Webmaster can then remove references to the Mist directory from the validated DAML file and move it to its official location. n 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 n Potential application for intelligence report representation (event- centric) n Populated sample file with events from 9/11 based on CNN chronology n Populated another sample with FBI chronology of Atta activities prior to attacks
21 Military Land Platform Ontology n Ontology focused on a taxonomy of equipment types n Ontology is modeled after Distributed Interactive Simulation (DIS) Entity Enumerations document
22 Ontology Development Commercial Shipping Ontology Define Commercial Ship Classes Subclasses Attributes Instance Data Authoritative Data Source Data Analysis & Decomposition
23 Foreign Clearance Guide n AFRL conducting research to reduce cost and time required to obtain clearances from foreign governments n Focused on lead times associated with diplomatic (DIP) clearances n Migrated IDEF1X data model to DAML+OIL ontology n Knowledge acquisition at Scott AFB in joint project with BBN
24 Equipment Characteristics and Performance n Equipment descriptions used by simulation applications for accurately representing platforms n Leveraged DRC work for Army Modeling and Simulation Office (AMSO) n Sample artifact developed based on Universal Threat System for Simulators (UTSS) sample data for AH-64A
25 DAML Development for UTSS Experiment n Created an Entity DAML ontology with Platform and Munitions (based on DIS Entity Enumeration taxonomy) n Created UTSS-specific DAML ontology tied to Platform ontology (i.e., A64A subclass of A64A class) n Translated UTSS data into DAML artifact / instance file
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