1. Model-based Data Engineering for Homeland Security Applications
Dr. Andreas Tolk College of Engineering and Technology
Old Dominion University

2. Education Hypothesis:
Homeland Security Applications require
A New Education Paradigm for System Engineers
Focusing on aligned contribution of solutions, which
Have been independently developed and
Are based on heterogeneous Infrastructures
Model-based Data Engineering is the first step towards required new Engineering Principles

3. Challenge of Homeland Security
Different supporting nations
Different supporting organizations (in the US 22)
Existing information technology
Supporting established business and organization rules
Organization and/or system specific data models (or XML tag sets)
Objective
Aligned multi-organization processes
Federation of heterogeneous IT solutions
Minimal changes to systems

4. Proposed Conceptual/Technical Solution
Model-based Data Engineering
Trading Data as a valuable resource
Applying engineering methods
Using a common reference model representing the understanding of information within the community of interest
Based on International Recommendations
NATO Code of Best for C2 Assessment
Adopted as a Standard by US OASD(NII)
Freely available by

5. Model-based Data Engineering uses a Common Reference Model
Data Administration
Which data is where
Formats, Interfaces, Technical accessibility
Security concerns, ownership
Data Management
Defining entities, attributes, relations
Standardized Data Elements
Data Alignment
Is the data needed on the receiving side available on the sending side
Data Transformation
Technical process of data mediation
Transforming data from sources into data needed on the consuming side
Model-based Data Engineering uses a Common Reference Model
(data understanding within the Community of Interest) to facilitate this tasks

6. LCIM Increasing Capability for Interoperation
Level 6 Conceptual Interoperability
Composability
Level 5 Dynamic Interoperability
Modeling / Abstraction
Level 4
Pragmatic Interoperability
Interoperability
Level 3
Semantic Interoperability
Increasing Capability for Interoperation
Simulation /
Implementation
Level 2
Syntactic Interoperability
Level 1
Technical Interoperability
Integretability
Level 0
No Interoperability
Network /
Connectivity

7. 3 4 5 6 2 1
CRM
Top-Down Approach
Identify organizations contributing towards a common operational goal
Conceptual model of participation comes from doctrine
Specific data vocabulary supporting doctrine from business rules
Bottom-Up Approach
Identify systems and data models supporting organizations
Apply Model-Based Data Engineering to allow common interchange of systems through CRM
Adapt Atomic, Composite, and Aggregate access from business rules- derived vocabulary to CRM
IT Systems can access CRM using Atomic, Composite or Aggregate Services

8. Summary of necessary steps
Model the supported processes of organizations
Align the processes top down
Who needs to work with whom
When is collaboration needed
Evaluate supporting system functionality
Which systems – and which system components and/or services – support the processes
Data Engineering
What data is needed, where do they come from?
Who owns the data, how can we access it?
What is the format, what is the logical meaning?
Data Mediation as a result of the work?

9. Peter O’Kelly (Burton Group): Data Modeling is Underrated: A Bright Future Ahead in the Grand Schema Things, Nov 30, 2006, Ontolog-Forum
© 2003 Burton Group. All rights reserved.

10. XML Data Mediation Services based on the CRM
(2) Data Administration 2
XML 1
(1) Data Modeling and Data Documentation - XML Document
Data Management - Mapping to CRM - Extending CRM - Enhancing CRM
CRM 3
(4) Data Alignment 4 !
(5) Data Transformation - Generate XSLT (+)
XSLT
XSLT (+) 5

11. XML Data Mediation Services based on the CRM
Other members of the COI
(1) Data Modeling and Data Documentation - XML Document 1
(2) Data Administration 1
XML
XSLT (+)
Data Management - Mapping to CRM - Extending CRM - Enhancing CRM
CRM
XML
XSLT (+) 1
XSLT (+)
XML
(4) Data Alignment
(5) Data Transformation - Generate XSLT (+)

12. Data Mediation Services
CRM
Concepts
Relations
Rules
Atomic Services
Composite Services
Aggregate Services
Data Mediation Services Application specific view
Aggregate Services Real aggregates
of information
Composition
of Information
Composite Services
Atomic Information
Atomic Services

13. Google Adapter C2 Linkopping
SitaWare C2 Norfolk
PABST M&S Meppen
WebCOP C2 Norfolk
SICF C2 Paris
C-BML Web Services
SIMBAD M&S Madrid
NATO MSG-027
PATHFINDER Integration Environment
Experiment C2-M&S Coupling
November 9, 2006

14. PABST
SICF
SIMBAD
SITAWARE

15. JEDIS DB JEDIS Web Service UOBDAT Authoritative Data Sources
Mediation Clients to CRM
Cohesive Data Product Repository
Mediation Clients for Data Consumers
Data Products
ACSIS
ASIT Client JCATS Init Products
JCATS Product Generator ASIT Client (JIDPS)
ASIT Client
Web Service
JEDIS DB
SGS
ASIT SGS Init Client
AWSIM Products Generator ASIT Client (SGS)
AWSIMASIT Client Init Products
JIDPS
JEDIS Web Service UOBDAT
JIDPS Client
UOBDAT
SIMPLE Products Generator ASIT Client (JIDPS)
ASIT Client SIMPLE Init Products
UOBDAT Client

16. Summary Data Engineering is recognized in various domains
Data Engineering results in direct support of Data Mediation Services needed for
Semantic Web Applications
Global Information Grid
Net-centric operations/Net-enabled Capabilities
Successful applications in NATO
MSG-027 Pathfinder Integration Environment
MSG-048 Coalition Battle Management Language
Related Standardization Efforts within SISO
Coalition Battle Management Language (C-BML)
Military Scenario Definition Language (MSDL)
Successful applications in JCOM
Joint Tactical Data Services (JTDS)
currently more then 1,000 services implemented used in the Joint Rapid Scenario Generation (JRSG) initiative in the Joint Advanced Training and Technology Laboratory (JATTL)

17. Selected References Invited Conference Paper:
Andreas Tolk, Charles Turnitsa, Saikou Diallo: “Model-Based Alignment and Orchestration of Heterogeneous Homeland Security Applications Enabling Composition of System of Systems,” Winter Simulation Conference WSC’07, Washington, DC, December 2007
Journal papers:
Andreas Tolk, Saikou Y. Diallo, Charles D. Turnitsa: “Applying the Levels of Conceptual Interoperability Model in Support of Integratability, Interoperability, and Composability for System-of-Systems Engineering,” Journal of Systemics, Cybernetics and Informatics, Volume 5 Number 5, pp , IIIS, 2007
Andreas Tolk, Charles D. Turnitsa, Saikou Y. Diallo: “Implied Ontological Representation within the Levels of Conceptual Interoperability Model,” International Journal of Intelligent Decision Technologies (IDT), Special Issue on Ontology Driven Interoperability for Agile Applications using Information Systems: Requirements and Applications for Agent Mediated Decision Support, Volume 2, Issue 1, January 2008
Andreas Tolk, Saikou Y. Diallo, Charles D. Turnitsa, Leslie S. Winters: “Composable M&S Web Services for Net-centric Applications,” Journal for Defense Modeling & Simulation (JDMS), Volume 3 Number 1, pp , January 2006
Andreas Tolk, Saikou Diallo: “Model-Based Data Engineering for Web Services,” IEEE Internet Computing Volume 9 Number 4, pp , July/August 2005
Invited Book Chapter:
Andreas Tolk, Saikou Y. Diallo: “Model-based Data Engineering for Web Services,” Chapter accepted for Lakhmi C. Jain (Ed.): Evolution of WEB in Artificial Intelligence Environment, Springer, 2008

18. Questions? Dr. Andreas Tolk Saikou Y. Diallo Charles D. Turnitsa
Associate Professor
College of Engineering & Technology
Department for Engineering Management
Old Dominion University
Norfolk, VA 23529
Saikou Y. Diallo Charles D. Turnitsa
Virginia Modeling Analyses & Simulation Center
Old Dominion University
7000 College Drive / Manning Bldg
Suffolk, VA 23435