C4ISR Data Ontology

1. C4ISR Data Ontology Presented by: Mr. George Herc RDECOM CERDEC Software Engineering Directorate In support of CELCMC SEC 06 April 2005

2. DoD Net-Centric Data Goals: Consumer Producer Searches metadata catalogs to find data Analyzes metadata to determine context of data found Pulls selected data based on understanding of metadata Describes content using metadata Posts metadatain catalogs and data in shared space Security Services (e.g., PKI, SAML) • Ensure data is: • Visible • Available • Understandable • Trusted • Interoperable • Responsive to users’ needs • Institutionalize Data Management Ubiquitous Global Network Metadata Catalogs Shared DataSpace Enterprise & Community Web Sites Application Services (e.g., Web) Metadata Registries COI / Developer Posts to and uses metadata registries to structure data and document formats for reuse and interoperability DoD Net-Centric Data Strategy Strategy enabled by COIs, metadata, registries, catalogs and shared data spaces

3. DoD Net-Centric Data Strategy Guidance DoD 8320.2: Data Sharing in a Net-Centric Department of Defense – December, 2004 • Puts in Policy DoD Data Strategy • The Heads of DoD Components shall: • Ensure implementation of Net-Centric data sharing, including establishing appropriate plans, programs, policies, processes, and procedures consistent with policies herein. • Ensure that all current and future data assets are made consistent with policies herein. • Support Mission Areas and Domains by taking an active role in COIs Mission Areas must form COIs to manage data CIO/G6 lead for implementing DoD 8320.2

4. Summary of Data Strategy Roles and Responsibilities • Define Domains and Domain owners; review Domain governance • Mission Area architecture and capability planning • Cross Mission Area and enterprise coordination • Manage Domain Portfolios and information capabilities • Ensure COI capabilities and Infrastructure are resourced • Domain architecture and capability planning; Identify Services • Facilitate information sharing among Domains • Develop semantic and logical agreements for data; register COI data schemas and models • Identify Authoritative Data Sources • Promote data sharing across the Enterprise • Tag Data with discovery metadata; make data available to “Shared Space” • Create searchable catalogs of data assets • Register metadata in appropriate registries, directories • Offer Services by planning and budgeting for services or capabilities to be exposed to the enterprise Reflects draft Army COI Policy and DODD 8320.2

5. DoD Net-Centric Goals and COI External Metrics DoD Goals External Metrics Visible Data posted/Data listed in catalogs Accessible Data available in shared space Data management follows relevant guidance Institutionalized Understandable Ontologies, taxonomies, content and format metadata developed Trusted Security data developed and posted/Authoritative Data Sources identified Interoperable Metadata registered/Data management follows mandated technical standards Responsive All stakeholders are members of COI

6. DoD Net-Centric Goals and their Meanings DoD Goals Meaning Visible Who has what data available? Accessible Where is this data and in what format? What and who governs the definition, lifecycle, and use of this data? Institutionalized Understandable What does this data mean? Trusted Is this data trustworthy, accurate, and authoritative? Interoperable Can my application use this data? Responsive Is this data timely?

7. Metadata Discovery Metadata Security Metadata COI-specific Ontologies Semantic Metadata Syntactic Metadata Content Metadata Structural Metadata Pedigree Metadata Shared Spaces Authoritative Data Sources Governance Oversight Processes/Practices Metrics/Incentives Education/Training Catalogs Services Communities of Interest Catalogs Metadata Registration Search Registries Asset Inventory Data Access Mediation User Feedback DoD Net-Centric Goals and Approaches Visible Accessible Institutionalized Understandable Trusted Interoperable Responsive

8. OBJECTIVE Define a C4ISR Data Ontology for the Integrated Data Environment being developed for the warfighter.

9. What is an Ontology • Metaphysics that studies the nature of existence • An ontology is a description (like a formal • specification of a program) of the concepts and relationships that can exist for an agent or a community of agents C4ISR Data Ontology • A specification mechanism for conceptualization of C4ISR interoperability data

10. C4ISR Data Ontology TECHNICAL APPROACH The C4ISR Data Ontology is being developed as an evolving baseline describing data exchanges performed by current message-based systems. • STATUS • Initial Ontology Complete • Translated C2IEDM v6.1 into OWL, • a W3C Ontology Language • Adding VID data to Initial Ontology • Aligning with DoD/Army Stakeholders USMTF = U.S. Message Test Format COI = Community of Interest VMF = Variable Message Format W3C = World-wide Web Consortium TDL = Tactical Data Link VID = VMF Integrated Database C2IEDM = C2 Information Exchange Data Model OWL = Web Ontology Language

11. UDDI (Discovery) Ontology Service Registry WSDL (Description) How to call Web Service Discover Web Service SOAP (Access) API for Web Service UDDI XML (Form) WSDL Application Web Service Access Web Service SOAP Receive Data Semantic Web:Dynamically Accessible Services UDDI = Universal Description, Discovery & Integration WSDL = Web Service Description Language SOAP = Simple Object Access Protocol

12. Ontologies Enable The Semantic Web • Interweave concepts & their representation • Capture semantics describing processes within domains • W3C languages provide common syntax for cross-domain information exchange

13. ISSUECurrent Systems Are Not Web-Enabled • Support tasks, not processes • Local optimization (vertical integration) • Lack enterprise perspective (horizontal integration) • Point-to-point data exchanges using military message formats • Difficult to implement • Expensive to maintain • Current systems must co-exist with new web-enabled systems • Same data is needed to support processes

14. C4ISR Data OntologyDescribes AS-IS Data Exchange • Translates IERs into a form useful to Data Modelers • Implemented in OWL, a W3C ontology language • Supports re-use: No need to re-engineer for each DM • Generates code: could be used as core for future Physical Data Models • Uses C2IEDM v6.1 for core concepts • C2 data used supporting multi-national operations • System-specific concepts flagged as potential extensions to C2IEDM • Supports IER refinement • Early identification of gaps • E.g., new data requirements introduced by system implementations • Eliminate need for rarely used data concepts. • Supports Net-Centric Data Strategy • Reduces need for pair-wise system-specific interfaces • Supports management of Net-Centric Checklists IER = Information Exchange Requirements

15. Ontologies Reduce # of Interfaces to Implement and Manage # Interfaces Equals # DMs 4 DMs means 3+2+1=6 Interfaces For 100 DMs: 4950 Interfaces (99+98+…)

16. Ontology-Driven Information Exchange Ontology & Inference Engine Current Systems Unchanged!

17. Data Modeling & Products Ontology & Inference Engine • Develop Data Products • IESS • Data Models • Ontology • Other as defined • Develop Web Applications • Inference Engines • Translation Services Current Systems Unchanged!

18. C4ISR Data Ontology • Created Initial Ontology from Existing C2IEDM • Converted to OWL, a W3C Ontology Language • Version 1: Expand Ontology to Include VMF Data • All messages identified for “minimum implementation” • Additional VMF messages supporting SWB-2 threads • Version 2: Expand Ontology to Include MTF Data • Leverage Air Force USMTF ontology work • Version 3: Expand Ontology to Include TDL Data

19. C4ISR Data OntologyApplies to Net-Centric Attributes ASD/NII Net Centric Checklist questions are designed to gather program information to assist DoD leadership in better understanding our move to net-centricity. Questions are tagged as Foundational [F] or Discovery [D]. • Foundational questions relate to a net-centric attribute • Discovery questions relate to how programs implement a feature. The DoD C4ISR Data Ontology Supports Foundational Issues

20. C4ISR Data Ontology • Translate IERs into a form useful to Data Modelers • Supports Re-use: No need to re-engineer for each COI’s DM • Generates code that can be used as core for Physical Data Model (SV-11) • Flexible, Conceptual Representation • Allows system-specific dialects • Keeps system-specific concepts hidden from other systems • Supports Net-Centric Data Strategy • Configuration managed organizationally aligned with Army COIs. • Configuration Management scales to DoD {and broader) enterprise scope. • Reduces Complexity • Reduces need for pair-wise system-specific (and COI-specific) interfaces • Objective identification of potential extensions to C2IEDM (and other core DMs) • Early identification of gaps • E.g., new data requirements introduced by system implementations • Supports IER refinement: Eliminate need for rarely used data concepts.

21. Communities of Interest (COIs) • COI is a set of stakeholders • Who must exchange information in pursuit of their shared • Goals • Interests • Missions • Business processes • Who must have shared vocabulary for the information they exchange COI define shared vocabulary, information to be shared, how it should be shared.

22. COI COI COI Formation – Institutional COI Functional Relationships • Institutional COI • Activity/Entity Based • Hierarchical • Reflects all Relationships • Based on Integrated Architectures • Functional Area (Data Developer) • Examples: C2, Sensors, Effectors, Logistics, Medical, Acquisition, etc Entity Relationships Army Enterprise must form Institutional COIs

23. Overlap Overlap Overlap Overlap Mission Thread Mission Thread COI Formation – Expedient COI Functional Relationships • Expedient COI • Thread Based • Capabilities Based • Cross-Domains/Functional • Reflects Partial Relationships • Based on Integrated Architectures • Data Consumer (use Functional Area standard vocabulary) • Examples: TST, JCAS, Global Strike, etc. Entity Relationships Systems Engineering and Governance of COI Boundaries Minimizes Overlap and Coupling Issues

24. Currently Registered COIs* • Computer Network Defense (CND) • Distribution COI • Force Projection • Global Force Management - Community of Interest (GFM-COI) • Information Operations • Joint Electronic Warfare Data Standardization WG • Joint Targeting Intelligence • MASINT Community of Interest • METOC (METEOROLOGY-OCEANOGRAPHY) • Modeling and Simulation Community of Interest • Sample COI Instructions • Space COI * From DoD Community of Interest Directory: https//extranet.itis.osd.mil/coi

25. Summary • DoD Net-Centric Data Strategy is now Policy (DoD 8320.2 & AR 25-1) • All must identify, prioritize, select information (data assets) to be shared with the enterprise, and designate authoritative data sources • Mission Areas and Domain leads must organize for battle by… • Forming and resourcing expedient COIs (lead/support joint & Army) • Forming Army Institutional COIs (focus area) • CIO-G6 is organized to support Data Strategy implementation of Mission Area & Domain leads with: • Services and Methodology (COI Administration, Data System Engineering, Data Modeling and products, Configuration Control, & Data Test Support) • Best Practices/Lessons Learned (COI Program Management Plan) • Policy & Guidance (Draft COI Policy, Draft COI Guidance Document, initial draft of Data Engineering Guidance Document, & DA PAM 25 1-1) • CIO-G6 teamed with Navy & Air Force to ensure common approach to implement Net-Centricity through Net-Centric Enterprise Support for Interoperability (NESI) • System Engineering and Integrated Architecture approach is required to execute Data Strategy. (CJCSI 3170 - JCIDS process) Data Strategy is critical but not sufficient to achieve Net-Centricity

26. Building Toward Shared Data Interoperability GAP Analysis Interoperability Assessment Register Data Products AV-2, OV-6a, OV-7, SV-6, SV-11, ADS, EIDs, XML Schema Systems Engineering & Integrated Architectures Create Common Vocabulary Identify Critical Business Transactions Identify Information Exchanges and Rules Identify Data Elements Meaning/Structure Identify Authoritative Data Sources Form COIs Define purpose, participants, expectations. Establish the relationships between COIs, Mission Area Leads, sub-domains, program managers, system owners and other data producers. Develop governance and funding requirements.