Recommended Approach for the FEA Data Reference Model (DRM)

1. Recommended Approach for the FEA Data Reference Model (DRM) Amit K. Maitra Consultant, Washington, DC October 19, 2005

2. Speaker’s Bio • Speaker’s Bio:Amit K. Maitra is an industry expert on the Federal Enterprise Data Architecture Framework. Mr. Maitra has over 20 years of experience in program planning, evaluation, and integration of Federal Enterprise Architectures under the Defense Information Systems Agency (DISA) Corporate Management Information (CIM) initiative; Department of State Enterprise Data Architecture initiative; and Customs Partnership (eCP) program of the Bureau of Customs and Border Protection (CBP), Department of Homeland Security (DHS). As Chief Enterprise Data Architect for eCP, Mr. Maitra was directly responsible for providing Enterprise Data Architecture support to the Bureau of Customs and Border Protection, with focus on identification, evaluation, preparation, and planning of CBP-DHS Strategic Interoperability and Business Line Implementation. Enterprise Architecture Programs.  • Additionally, he was actively involved with the Industry Advisory Council Enterprise Architecture Special Interest Group in providing industry best practices recommendations to the Office of Management and Budget Federal • Information sharing, according to the DRM, can be enabled through the common categorization and structure of data. Contrary to the prevailing notion, however, this presentation argues that a better DRM solution lies in a Model Driven Architecture (MDA) framework that: •  Mr. Maitra is a Senior Enterprise Data Architect for Federal programs; his current interests include the preparation, identification and planning of wireless components for a FEAF-based enterprise architecture. Incorporating the mission requirements of the customer, a large Federal agency, these components are customized to reflect the agency's FEAF-compliant wireless and wireless geospatial needs and will facilitate horizontal and vertical integration across and beyond the agency's boundaries. Amit K. Maitra

3. CONTEXT • Global Environment • Changing Technologies • Revolutionary Moments: The Mandate • The Current Situation • The Solution: The DRM • The Architecture • The Structure • The Tools • Federated Data Management Approach • The Result • Paradigm Shift • Concern • Leadership at DoD • Decisions: Net Centric Data Strategy & Community of Interest • Processes: NCDS & COI Amit K. Maitra

4. Underlying Theme • Fully integrated information systems for a shared data environment Amit K. Maitra

5. Focus • Information, Access, Authorization, Emerging Technologies • Data Accessibility, Commonality, and Compatibility Design • Data Dictionary • Data Quality • Security & Privacy Assurance Amit K. Maitra

6. Global Environment • Characteristics • Geographically distributed, dissimilar elements of varying capabilities and responsibilities • Data distributed to and redistributed among system facilities, interconnected by both private and shared public communications networks Amit K. Maitra

7. Changing Technologies • A Gentle Transition From XML to Resource Description Framework (RDF) • The purpose of RDF is to give a standard way of specifying data “about” something • Advantage of using RDF • If widely used, RDF will help make XML more interoperable • Promotes the use of standardized vocabularies ... standardized types (classes) and standardized properties • Provides a structured approach to designing XML documents • The RDF format is a regular, recurring pattern • Quickly identifies weaknesses and inconsistencies of non-RDF-compliant XML designs • Helps us better understand our data! • Positions data for the Semantic Web! Amit K. Maitra

8. Changing Technologies: Web Ontology Language (OWL) • RDF has limited expressive capability • -- Mostly limited to taxonomic descriptions • The things we model have complex relationships so we need to capture many different facets, or restrictions on class and property descriptions Amit K. Maitra

9. Revolutionary Moments: The Mandate “Our success depends on agencies working as a team across traditional boundaries to serve the American people, focusing on citizens rather than individual agency needs.” ~ President George W. Bush Amit K. Maitra

10. The Current Situation: The Federal Government is less than efficient in performing its business and meeting customer needs due to data sharing inefficiencies caused by stove-piped data boundaries Primary Issues and Information Sharing Barriers Stove-Piped Data Boundaries “As Is State” • No common framework or methodology to describe the data and information that supports the processes, activities, and functions of the business • No definition of the handshake or partnering aspects of information exchange • Existing systems offer diffused content that is difficult to manage, coordinate, and evolve • Information is inconsistent and/or classified inappropriately • Without a common reference, data is easier to duplicate than integrate • No common method to share data with external partners • Limited insight into the data needs of agencies outside the immediate domain • Data and Information context is rarely defined • Stove piped boundaries, no central registry • Lack of funding and incentive to share • Data sensitivity and security of data • New laws/issues result in continuous adding of databases that can not share data Illustrative INDUSTRY HHS DHS Have Created FDA CDC INS TSA USDA ENERGY DOI LABOR Denotes data and information sets within agencies. Amit K. Maitra

11. Subject Area Data Classification Data Object Data Property Data Representation The Solution: The Data Reference Model (DRM) The DRM provides: • A framework to enable horizontal and vertical information sharing that is independent of agencies and supporting systems • A framework to enable agencies to build and integrate systems that leverage data from within or outside the agency domain • A framework that facilitates opportunities for sharing with citizens, external partners and stakeholders Amit K. Maitra

12. MODEL DRIVEN ARCHITECTURE The Architecture • A virtual representation of all physical data sources: • - Applications are to be decoupled from data sources • - Details of data storage and retrieval are to be abstracted • - Are to be easily extended to new information sources Amit K. Maitra

13. The Structure META OBJECT FACILITY Amit K. Maitra

14. The Tools Amit K. Maitra

15. Federated Data Management Approach Amit K. Maitra

16. The Result: Interagency Information Federation Amit K. Maitra

17. Paradigm Shift • MDA is fundamental change • MDA rests on MOF • It is the best architecture for integration • It shifts data architecture from Entity Relationship Diagramming (ERD) to a Business Context (Interoperability/Information Sharing) Business & Performance Driven Approach Amit K. Maitra

18. Concerns • To what extent the government agencies, Customers, Partners are willing to participate along the Lines of Business (LOB), thereby underscoring the importance of working toward a common goal: Collective Action IAW National Security/National Interests criteria • These need to be tested and validated against uniquely tailored performance indicators: Inputs, Outputs, and Outcomes Amit K. Maitra

19. Leadership at DoD • Decisions • Processes Amit K. Maitra

20. Decisions “Net-Centric Data Strategy& Communities of Interest (COI)” Amit K. Maitra

21. B A R R I E R B A R R I E R B A R R I E R B A R R I E R Processes: The DoDNet-Centric Data Strategy aims at breaking down barriers to information sharing… End-User Producer End-User Consumer “What data exists?“ “How do I access the data?” “How do I know this data is what I need?” “How can I tell someone what data I need?” “How do I share my data with others?” “How do I describe my data so others can understand it?” User knows data exists and can access it but may not know how to make use of it due to lack of under- standing of what data represents User is unaware this data exists User knows this data existsbut cannot access itbecause of organizational and/or technical barriers ? Organization “A” Organization “B” Organization “C” Amit K. Maitra

22. The Net-Centric Data Strategy is a key enabler of the Department’s transformation... • The Strategy (signed May 9, 2003) provides the foundation for managing the Department’s data in a net-centric environment, including: • Ensuring data are visible, accessible, and understandable when needed and where needed to accelerate decision making • “Tagging” of all data (intelligence, non-intelligence, raw, and processed) with metadata to enable discovery by known and unanticipated users in the Enterprise • Posting of all data to shared spaces for users to access except when limited by security, policy, or regulations • Organizing around Communities of Interest (COIs) that are supported by Warfighting, Business, Enterprise Information Environment, and Intelligence Mission Areas and their respective Domains. The Strategy describes key goals to achieving net-centric data management… Amit K. Maitra

23. Tag data assets with COI-defined metadata that enables it to be searched (visible) Organize data assets using taxonomies developed by experts within the COI Define the structure and business rules for operating with data and information (e.g. define data models, schema, interfaces) Identify, define, specify, model, and expose data assets to be reused by the Enterprise as services Key Goals Make Data Visible Make Data Accessible Enable Data to be Understandable Enable Data to be Trusted Enable Data Interoperability COIs are a key ‘implementer’ of data strategy goals… Key COI Actions: Amit K. Maitra