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Semantic Web Applications for Modeling and Simulation

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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 ... – PowerPoint PPT presentation

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Title: Semantic Web Applications for Modeling and Simulation


1
Semantic Web Applications for Modeling and
Simulation
Lee W. Lacy Dynamics Research Corporation
Captain Joel Pawloski U.S. Army TRAC-M
  • July 11, 2001
  • DMSO Technical Exchange Meeting

2
Agenda
  • Web Technology Evolution
  • XML MS Applications
  • U.S. Army TRAC-M XML Research
  • Semantic Web Background
  • DARPA Semantic Web Research
  • Potential Semantic Web MS and C4I Applications

3
The Evolving Web
Web of Knowledge
Proof, Logic and Ontology Languages (e.g.,
DAMLOIL)
Shared terms/terminology Machine-Machine
communication
2010
Resource Description Framework (RDF) eXtensible
Markup Language (XML)
Self-Describing Documents
2000
HyperText Markup Language (HTML) HyperText
Transfer Protocol (HTTP)
Formatted Documents Foundation of the Current Web
1990
Based on Berners-Lee, Hendler Nature, 2001
4
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

5
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

6
XML DIF Method
ModSAF
XML-based Data Interchange File (DIF)
Janus
CCTT
7
MS 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

8
Specific U.S. Army MS XML Research Initiatives
  • Military Scenario Definition Language (MSDL)
  • Computer Generated Forces (CGF) Behaviors
  • Equipment Characteristics and Performance (CP)

9
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

10
Scenario Content Analysis
  • Metadata
  • Environment
  • Organization
  • Simulation Object
  • Information Item
  • Events
  • Unassigned

11
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)

12
MSDL Schema
  • Defined using XML DTD and XML Schema
  • Sample scenarios marked up

13
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

14
Current CGF Systems
15
Perfect World Behavior Sharing
System 1
System 2
Behaviors Represented in Common Language Using
XML
System 3
System 4
16
CGF Behavioral Representation Logical Data Model
Components
17
SIMTECH Demonstration
18
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
  • ltmaxspeed unitsmphgt45lt/maxspeedgt vs.
  • ltparametergt ltnamegtmaxspeedlt/namegt ltunitsgtmphlt/u
    nitsgt ltvaluegt45lt/valuegt lt/parametergt

19
Semantic Problems for XML
  • Synonymy and polysemy
  • ltPERSONgt vs. ltINDIVIDUALgt
  • is ltSPIDERgt an arachnid or software?
  • Structural differences
  • ltPERSONgtltNAMEgtLee Lacylt/NAMEgtltPERSONgt vs.
  • ltPERSONgtltNAMEgt ltFNAMEgtLeelt/FNAMEgt ltLNAMEgtLacylt/
    LNAMEgt lt/NAMEgtlt/PERSONgt

Based on Hendler, 2001
20
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

21
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

22
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

23
What is an Ontology?
Thesauri narrower term relation
Frames (properties)
General Logical constraints
Formal is-a
Catalog/ ID
Informal is-a
Formal instance
Disjointness, Inverse, part-of
Terms/ glossary
Value Restrs.
TAXONOMY
ONTOLOGY
Based on McGuinness, 2001 http//www.daml.org/2
001/06/swday-ontologies/Ontologies-talk-060401_fil
es/frame.htm
24
Beyond XMLAgent Semantics
  • DARPA developing an Agent Markup Language (DAML)
  • A semantic language that ties the information
    on a page to machine readable semantics (ontology)

25
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

26
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

27
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
28
Layered Architecture

DAMLOIL
DC
PICS
XHTML
SMIL
RDF(S)
HTML
XML(S)
Based on Horrocks, 2001 http//www.cs.man.ac.uk/
horrocks/Slides/
29
DAML Status
  • DAMLOIL 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
    www-rdf-logic_at_w3.prg
  • Denotational (and axiomatic) Semantics published
  • First formal semantics for a web language
  • Proposal to W3C for standardization ongoing

30
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

31
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

32
CALL Thesaurus Ontology
Term
33
Military Equipment Ontology
  • Army Military Equipment Characteristic
    Performance (CP) 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)

34
DAML Query Demonstration
  • Semantic web DAML Demonstration
  • Uses Call Thesaurus and Military Equipment CP
    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

35
DAML Query Demonstration
36
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)

37
Intelligence Report Ontology
INNOVATIVE SOLUTIONS THROUGH PEOPLE, PROCESSES,
AND TECHNOLOGY
38
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
    sponsors goals paramount but will affect
    usefulness of cross-ontology joins

39
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

40
Potential MS 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

41
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
    MS-related SW applications can link to terms

42
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)

43
BML Thoughts
  • BML Users 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., Users
    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

44
Preliminary BML Order Ontology
45
Summary
  • Web technology continues to evolve
  • XML is being used for MS applications
  • Semantic Web technologies emerging that provide
    potential solutions to DoD MS challenges
  • Research and proof-of-concept demonstrations
    needed to show benefits

46
Questions?Lee LacyLLacy_at_DRC.com
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