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 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

3. The Evolving Web 2010 2000 1990 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)
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. 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

8. 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)

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
WARSIM
CCTT
ModSAF
Ada Finite State Machines
Asynchronous Augmented Finite State Machines (translated into “C” code)
Behavioral Description Frames
Fundamental Behaviors (C++ code)
Today’s CGF systems are built in a stove-piped manner

15. “Perfect World” Behavior Sharing
System #1
System #2
Behaviors
Represented in
Common Language
Using XML
System #3
System #4
In a perfect world, we’d all speak the
same language

16. CGF Behavioral Representation Logical Data Model Components
Behavior Specification
Logical Data Model Components
Knowledge Representation
Constructs
Complexity
Metadata
Declarative
Procedural
Strategic

17. SIMTECH Demonstration
Equipment
Characteristics and
Performance Data
in XML
AMSAA
NGIC
OTB
Combat
XXI

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
<maxspeed units=“mph”>45</maxspeed> vs.
<parameter> <name>maxspeed</name> <units>mph</units> <value>45</value> </parameter>

19. 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

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. Disjointness, Inverse, part-of…
What is an Ontology?
Thesauri
“narrower
term”
relation
Frames
(properties)
Formal
is-a
General
Logical
constraints
Catalog/ ID
Informal
is-a
Formal
instance
Disjointness, Inverse, part-of…
Terms/
glossary
Value Restrs.
TAXONOMY
ONTOLOGY
Based on McGuinness, 2001:

24. 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)

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
Semantic Web Res. (EU)
W3C
DAML
C2 link
RDF
XML
RDF-S
DAML-ONT
DAML-LOGIC
US/EU Joint Efforts
(S. Decker, Coord)
Horus
Research efforts:
SHOE
OIL
EC OntoWeb
Intl Workshops
Tools
Lang Spec
Demos
Ctr for Army
Lessons Learned
EU W3C
Members/directors
(Dan Brickley, coord)
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 DAML+OIL DC PICS XHTML SMIL RDF(S) HTML XML(S)
Based on Horrocks, 2001:

29. 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:
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
name
CALL
Term
descriptorFor RT
domain
subClassOf
inverseOf
subPropertyOf
range & domain
Legand
preferred
TermFor BT NT
ACK AF
entry
TermFor
USE UF

33. 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)

34. 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

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
Event
Location
Area
Timeframe
Activity
Equipment
Organization
Person
Description
Note
Intelligence
Report
Conclusion
Building
Metadata
Terrorist
subclassOf
partOf
describedAs
locatedIn
within
memberOf
Vehicle
Motorcycle
Automobile
drivenBy
Country
resultedIn
conclusion
metadata
event
conclusionEvent
Subject, directObject, indirectObject, source
Subject
directObject
indirectObject
regarding
source
timeframe
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 sponsor’s 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 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

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 M&S-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 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

44. Preliminary BML Order Ontology
Timeframe
Operation
Formation
Task
Unit
partOf
Location
takesPlaceAt
layedOutIn
takesPlaceWithin
arrangedAt
supports
performs

45. 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

46. Questions? Lee Lacy LLacy@DRC.com