Transcript Semantic Web Applications for Modeling and Simulation

Semantic Web Applications for
Modeling and Simulation
Lee W. Lacy
Dynamics Research Corporation
Captain Joel Pawloski
U.S. Army TRAC-M
TRAC-Monterey
July 11, 2001
DMSO Technical Exchange Meeting
Agenda
Dynamics Research Corporation
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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
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The Evolving Web
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Web of
Knowledge
Proof, Logic and
Ontology Languages
(e.g., DAML+OIL)
Shared terms/terminology
Machine-Machine
communication
2010
Resource Description Framework (RDF)
eXtensible Markup Language (XML)
HyperText Markup Language
(HTML)
HyperText Transfer Protocol
(HTTP)
Self-Describing Documents
2000
Formatted Documents
Foundation of the Current Web
1990
Based on Berners-Lee, Hendler; Nature, 2001
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Hypertext Markup Language (HTML)
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• 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
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eXtensible Markup Language (XML)
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• 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
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XML DIF Method
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ModSAF
Janus
XML-based
Data Interchange
File (DIF)
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CCTT
M&S and C4I use of XML
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• 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
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Specific U.S. Army M&S XML
Research Initiatives
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• Military Scenario Definition Language (MSDL)
• Computer Generated Forces (CGF) Behaviors
• Equipment Characteristics and Performance (C&P)
TRAC-Monterey
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MSDL Objectives
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• 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
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Scenario Content Analysis
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Metadata
Environment
Organization
Simulation Object
Information Item
Events
Unassigned
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MSDL Standard
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• 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)
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MSDL Schema
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• Defined using XML
DTD and XML Schema
• Sample scenarios
marked up
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CGF Behaviors
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• 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
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Current CGF Systems
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ModSAF
CCTT
•Ada Finite State
Machines
•Asynchronous
Augmented Finite State
Machines (translated
into “C” code)
WARSIM
•Behavioral Description
Frames
•Fundamental Behaviors
(C++ code)
Today’s CGF systems are built in a stove-piped manner
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“Perfect World” Behavior Sharing
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System
#1
System
#3
System
#2
Behaviors
Represented in
Common Language
Using XML
System
#4
In a perfect world, we’d all speak the
same language
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CGF Behavioral Representation Logical
Data Model Components
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Behavior Specification
Logical Data Model Components
Knowledge Representation
Constructs
Declarative
Complexity
Metadata
Procedural
Strategic
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SIMTECH Demonstration
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OTB
AMSAA
Equipment
Characteristics and
Performance Data
in XML
NGIC
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Combat
XXI
Explicit vs. Metamodel Schemas
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• 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>
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Semantic Problems for XML
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• 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
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Resource Description Framework (RDF)
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• 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
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Why RDF Is Not Enough
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• 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
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Semantic Web (SW)
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• 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
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What is an Ontology?
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Catalog/
ID
Thesauri
“narrower
term”
relation
Informal
is-a
Terms/
glossary
TAXONOMY
Frames General
Formal
is-a (properties) Logical
constraints
Formal
instance
Disjointness,
Value Inverse, partRestrs. of…
ONTOLOGY
Based on McGuinness, 2001:
http://www.daml.org/2001/06/swday-ontologies/Ontologies-talk-060401_files/frame.htm
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Beyond XML:Agent Semantics
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• DARPA developing an Agent Markup
Language (DAML)
– A “semantic” language that ties the
information on a page to machine readable
semantics (ontology)
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DARPA DAML Research Team
Dynamics Research Corporation
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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
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Benefits
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• 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
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A new/old model of DoD partnering
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DARPA:
www.semanticweb.org
Research efforts:
 Funds a new
SHOE
OIL
EC OntoWeb
generation of www
technology
Intl Workshops
 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
Semantic Web Res. (EU)
EU W3C
Members/directors
(Dan Brickley, coord)
Tools
US/EU Joint
Efforts
(S. Decker,
Coord)
Lang Spec
RDF
C2 link
Demos
Horus
RDF-S
XML
W3C
www.w3.org/RDF/
DAML-ONT
DAML-LOGIC
Ctr for Army
Lessons Learned
www.daml.org
Based on Hendler, 2001
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DAML
Layered Architecture
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DAML+OIL
DC
XHTML
HTML
SMIL
RDF(S)
XML(S)
Based on Horrocks, 2001: http://www.cs.man.ac.uk/~horrocks/Slides/
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PICS
DAML Status
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• 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 protected]
– Denotational (and axiomatic) Semantics published
• First formal semantics for a web language
– Proposal to W3C for standardization ongoing
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www.DAML.org
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• 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
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DAML Military Examples
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• 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
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CALL Thesaurus Ontology
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Term
Legand
name
domain
descriptorFor
CALL
Term
range & domain
RT
subClassOf
inverseOf
preferred
TermFor
entry
TermFor
subPropertyOf
BT
NT
ACK
AF
USE
UF
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Military Equipment Ontology
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• 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)
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DAML Query Demonstration
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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
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DAML Query Demonstration
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HUMINT Report Representation
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• Unclassified Force Protection Sample HUMINT
report provided
• Classes identified included:
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Organization, Person (who)
Activity, Event (what)
Timeframe (when)
Location Area (where)
Conclusion (why)
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Intelligence Report Ontology
Intelligence
Report
conclusion
metadata
event
Organization
Conclusion
partOf
Metadata
conclusionEvent
subclassOf
describedAs
Person
Description
memberOf
Terrorist
Organization
Person
source
locatedIn
Location
Area
Equipment
locatedIn
subclassOf
drivenBy
Building
Vehicle
subclassOf
Automobile
within
regarding
Event
Note
Subject,
directObject,
indirectObject,
source
Activity
subclassOf
Country
Timeframe
resultedIn
Subject
directObject
indirectObject
subclassOf
Motorcycle
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timeframe
Ontology Design Issue
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• 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”
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Potential Encoding Sources
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• Events:
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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
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Potential M&S Applications of Semantic
Web Technologies
Dynamics Research Corporation
• 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
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CSS Thoughts
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• 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
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Battle Management Language
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• 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:
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Unit identification (who)
Operation / Task (what)
Operation time (when)
Operation location (where)
Operation purpose / mission (why)
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BML Thoughts
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• 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
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Preliminary BML Order Ontology
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partOf
Unit
Task
layedOutIn
performs
performs
supports
Operation takesPlaceAt
Formation
arrangedAt
Location
takesPlaceWithin
Timeframe
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Summary
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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
• Research and proof-of-concept demonstrations
needed to show benefits
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Dynamics Research Corporation
Questions?
Lee Lacy
[email protected]
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