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

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

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

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 http://www.dodccrp.org

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

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

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

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?

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.

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

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 (+)

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

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

PABST SICF SIMBAD SITAWARE

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

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)

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. 65-74, 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. 27-44, January 2006 Andreas Tolk, Saikou Diallo: “Model-Based Data Engineering for Web Services,” IEEE Internet Computing Volume 9 Number 4, pp. 65-70, 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

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 atolk@odu.edu Saikou Y. Diallo Charles D. Turnitsa Virginia Modeling Analyses & Simulation Center Old Dominion University 7000 College Drive / Manning Bldg Suffolk, VA 23435 [sdiallo,cturnits@odu.edu]