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Lacy Dynamics Research Corporation Captain Joel Pawloski U.S. Army TRAC-M Agenda : Agenda Web Technology Evolution XML M&S Applications U.S. Army TRAC-M XML Research Semantic Web Background DARPA Semantic Web Research Potential Semantic Web M&S and C4I Applications The Evolving Web : The Evolving Web Web of Knowledge HyperText Markup Language (HTML) HyperText Transfer Protocol (HTTP) Resource Description Framework (RDF) eXtensible Markup Language (XML) Self-Describing Documents Formatted Documents Foundation of the Current Web Proof, Logic and Ontology Languages (e.g., DAML+OIL) Shared terms/terminology Machine-Machine communication 1990 2000 2010 Based on Berners-Lee, Hendler; Nature, 2001 Hypertext Markup Language (HTML) : Hypertext Markup Language (HTML) Enabled standard communication of content combined with format Loosely defined specific (limited) grammar specified using SGML (specific language) Started by Tim Berners-Lee Standardized by World-Wide Web Consortium (W3C) Ubiquitous method of presenting and communicating data Used throughout DoD on both public internet and SIPRNET and other classified networks Not useful for machine search eXtensible Markup Language (XML) : eXtensible Markup Language (XML) Separates content from format (standard syntax) Simplified version of SGML (metalanguage) for defining eXtensible tag sets Started by Tim Bray et al based on conversations with Tim Berners-Lee Standardized by W3C Used to define updated HTML grammar (XHTML) Used in Modeling and Simulation community primarily for Data Interchange Formats (DIFs) that support data sharing XML DIF Method : XML DIF Method Janus CCTT ModSAF XML-based Data Interchange File (DIF) M&S and C4I use of XML : M&S and C4I use of XML HLA Data Interchange Formats (DIFs) JSIMS Common Component Workstation Battlespace Schema Combat XXI Scenario Files OneSAF Objective System Land Warrior User Interface Specifications Joint C4ISR Integration Facility (JCIF) Joint Battlespace Infosphere (JBI) XML Assessment Specific U.S. Army M&S XML Research Initiatives : Specific U.S. Army M&S XML Research Initiatives Military Scenario Definition Language (MSDL) Computer Generated Forces (CGF) Behaviors Equipment Characteristics and Performance (C&P) MSDL Objectives : MSDL Objectives Support Scenario Developers Improve Scenario Quality Reduce Time to Develop Scenarios Reduce Costs of Developing Scenarios Support Scenario Generation Tool Developers Reduce Tool Development Costs Improve Tool Interoperability Scenario Content Analysis : Scenario Content Analysis Metadata Environment Organization Simulation Object Information Item Events Unassigned MSDL Standard : MSDL Standard Initial work reviewed by Combat XXI Combat XXI enhancements merged into Army Modeling and Simulation Office (AMSO) Standards Nomination and Approval Process (SNAP) submission SNAP submission serving as starting point for OneSAF Objective System (OOS) MSDL Schema : MSDL Schema Defined using XML DTD and XML Schema Sample scenarios marked up CGF Behaviors : CGF Behaviors Computer Generated Forces (CGF) systems simulate units and platforms CGF systems operate at a variety of fidelity and resolution levels Behaviors historically “hard coded” Newer systems represent behaviors in data Considerable resources required to develop CGF systems and their associated behaviors Current CGF Systems : Current CGF Systems “Perfect World” Behavior Sharing : “Perfect World” Behavior Sharing Behaviors Represented in Common Language Using XML System #3 System #1 System #2 System #4 CGF Behavioral Representation Logical Data Model Components : CGF Behavioral Representation Logical Data Model Components SIMTECH Demonstration : SIMTECH Demonstration Explicit vs. Metamodel Schemas : Explicit vs. Metamodel Schemas XML DTD and/or XML Schema design often involves decisions over the use of explicit tags or representation of names in data <maxspeed units=“mph”>45</maxspeed> vs. <parameter> <name>maxspeed</name> <units>mph</units> <value>45</value> </parameter> Semantic Problems for XML : Semantic Problems for XML Synonymy and polysemy <PERSON> vs. <INDIVIDUAL> is <SPIDER> an arachnid or software? Structural differences <PERSON><NAME>Lee Lacy</NAME><PERSON> vs. <PERSON><NAME> <FNAME>Lee</FNAME> <LNAME>Lacy</LNAME> </NAME></PERSON> Based on Hendler, 2001 Resource Description Framework (RDF) : Resource Description Framework (RDF) RDF data consists of nodes and attached attribute/value pairs Nodes can be any web resources Attributes are named properties of nodes Values are either atomic (text strings, numbers, etc.) or other resources or metadata instances Supports labeled directed graphs XML used as graph serialization syntax for storing and communicating RDF instances Provides basic ontological primitives Classes and relations (properties) Class (and property) hierarchy RDF triples assert facts about resources Why RDF Is Not Enough : Why RDF Is Not Enough Expressive inadequacy Only range/domain constraints (on properties) No properties of properties (unique, transitive, inverse etc.) No equivalence, disjointness, coverings etc. No necessary and sufficient conditions (for class membership) Poorly (un) defined semantics Semantic Web (SW) : Semantic Web (SW) Provides agent-readable descriptions of data, information, and knowledge Built on top of XML and RDF Envisioned by Tim Berners-Lee and researched by DARPA team and others W3C is beginning a Semantic Web initiative Used to define ontologies and associated instance data Huge potential for Modeling and Simulation community What is an Ontology? : What is an Ontology? Catalog/ ID General Logical constraints Terms/ glossary Thesauri “narrower term” relation Formal is-a Frames (properties) Informal is-a Formal instance Value Restrs. Disjointness, Inverse, part-of… TAXONOMY ONTOLOGY Based on McGuinness, 2001: http://www.daml.org/2001/06/swday-ontologies/Ontologies-talk-060401_files/frame.htm Beyond XML:Agent Semantics : Beyond XML:Agent Semantics DARPA developing an Agent Markup Language (DAML) A “semantic” language that ties the information on a page to machine readable semantics (ontology) DARPA DAML Research Team : DARPA DAML Research Team BBN Booz-Allen and Hamilton Cycorp Dynamics Research Corporation (DRC) GRCI Lockheed Martin Management and Data Systems SRI Teknowledge Carnegie Melon University University of Southern California Information Sciences Institute MIT (W3C) Stanford University UMBC University of West Florida Yale University Benefits : Benefits Standard representation of “object-oriented” concepts across the web Extensibility of ontologies through namespaces Support for complex queries involving “semantic joins” over multiple data sets A new/old model of DoD partnering : A new/old model of DoD partnering DARPA: Funds a new generation of www technology Works closely with W3C to create a web standard Works closely with EU on international acceptance Brings DoD users (J2,J3,J6) in as early adopters Based on Hendler, 2001 Layered Architecture : Layered Architecture DAML+OIL HTML XHTML XML(S) SMIL RDF(S) DC PICS Based on Horrocks, 2001: http://www.cs.man.ac.uk/~horrocks/Slides/ DAML Status : DAML Status DAML+OIL ontology language released on World Wide Web Annotated “walkthrough” Examples Full definition RDFS = Resource Description Framework Schema Provides 100% mapping to XML Open discussion group run by W3C: email@example.com Denotational (and axiomatic) Semantics published First formal semantics for a web language Proposal to W3C for standardization ongoing www.DAML.org : www.DAML.org Language Specifications DAML Newsletter (you can subscribe) Collection of web tools Ontology library 157 ontologies as of July 9, 2001 DAML crawler over 14,000 pages w/2,000,000+ DAML statements, 5/15/01 Web tracking software used for baselining DAML use Over 500,000 hits in first 6 months DAML Military Examples : DAML Military Examples Army CALL Thesaurus Army Equipment (based on WARSIM Equipment Knowledge Acquisition Tool schema) Military task lists (e.g., UJTL) – under development Army CALL University After Next (UAN) Warrior Knowledge Network (WKN) Human Intelligence (HUMINT) interrogation procedure representation – just started Intelink (DIA) HUMINT report representation – small sample developed – currently extending CALL Thesaurus Ontology : CALL Thesaurus Ontology Term Military Equipment Ontology : Military Equipment Ontology Army Military Equipment Characteristic & Performance (C&P) Ontology Provides framework to compose Army equipment from the System Unit to individual component (i.e., radio) level Ontology is modeled after data model used by WARSIM and that housed by the FDB (Functional Description of the Battlespace) DAML Query Demonstration : DAML Query Demonstration Semantic web DAML Demonstration Uses Call Thesaurus and Military Equipment C&P ontologies and data to demonstrate the potential of the semantic web Demonstration is composed of: Thesaurus Lookup Term Military Equipment Lookup Complex query involving multiple ontologies by using thesaurus lookup results to find military equipment terms DAML Query Demonstration : DAML Query Demonstration HUMINT Report Representation : HUMINT Report Representation Unclassified Force Protection Sample HUMINT report provided Classes identified included: Organization, Person (who) Activity, Event (what) Timeframe (when) Location Area (where) Conclusion (why) Intelligence Report Ontology : Intelligence Report Ontology INNOVATIVE SOLUTIONS THROUGH PEOPLE, PROCESSES, AND TECHNOLOGY Ontology Design Issue : Ontology Design Issue Explicit description of classes vs. encoding of information as data Explicit definition: Requires extensive maintenance of ontology Supports complex queries Encoding: Requires companion encoding standard (e.g., DIS enumeration document, SEDRIS environmental data coding specification) Decision will be made on case-by-case basis with sponsor’s goals paramount but will affect usefulness of cross-ontology “joins” Potential Encoding Sources : Potential Encoding Sources Events: Fineberg Verb Taxonomy Kansas Event Data System (KEDS) World Events Interaction Survey (WEIS) Codes BML operations / tasks UJTL / service task lists Things: FDMS taxonomy DIS Enumeration Document Potential M&S Applications of Semantic Web Technologies : Potential M&S Applications of Semantic Web Technologies Human Behavior Representation (e.g., CHRIS) Glossaries / Taxonomies / Thesauri (e.g., CSS) CGF Behavior Development (e.g., TRAC-M research effort) Knowledge Acquisition (e.g., FDMS) METL development (e.g., JTIMS) Scenario Development (e.g., MSDL) Unit Order of Battle (e.g., UOB DAT) Data Provisioning (e.g., AMSO SIMTECH effort) HLA FEDEP Tool Architecture (e.g., DIFs) Web Services (e.g., fly-out model responsibility) AAR / logger data CSS Thoughts : CSS Thoughts DMSO CSS provides definitions, unlike Army CALL thesaurus DAML thesaurus ontology based on ANSI standard for representing thesauri information CSS validated and traceable to Authoritative Data Sources (ADSs) DAML thesauri ontology could be extended to support definitions and ADS traceability CSS could be “ported” to semantic web instance data Once represented as SW content, terms can be manipulated using standard SW tools and other M&S-related SW applications can link to terms Battle Management Language : Battle Management Language Standard verbiage or vocabulary used by simulation programmers or workstation controllers to describe planning and executing military functions currently performed by human controllers Key factors supporting automated Course of Action (COA) analysis: Unit identification (who) Operation / Task (what) Operation time (when) Operation location (where) Operation purpose / mission (why) BML Thoughts : BML Thoughts BML User’s Guide Annex A contains CSS-like definitions Value of BML is in knowledge representation structure developed (i.e., units, timeframe, etc.) and specified vocabulary (i.e., User’s Guide Annex A) BML KR structure could be used as the basis for an ontology for orders BML vocabulary could be migrated into ontology instance data similarly to CSS Preliminary BML Order Ontology : Preliminary BML Order Ontology Summary : Summary Web technology continues to evolve XML is being used for M&S applications Semantic Web technologies emerging that provide potential solutions to DoD M&S challenges Research and proof-of-concept demonstrations needed to show benefits Questions?Lee LacyLLacy@DRC.com : Questions?Lee LacyLLacy@DRC.com You do not have the permission to view this presentation. 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