Implementing the Federal Enterprise Architecture Data Reference Model (FEA DRM)

1. Implementing the Federal Enterprise Architecture Data Reference Model (FEA DRM) How to Manage Data Across Agencies Using the FEA DRM 11 September 2006 “Build to Share”

2. Agenda • FEA DRM Basic Concepts • Three Pillar Data Strategy Framework • Federal Data Architecture Subcommittee • Agency DRM Implementation Examples

3. How do I exchange the data? Data Sharing Query Points and Exchange Packages How do I find the data and access it? What does the data mean? Data Description Data Context Taxonomies Data FEA DRM Concept Based on FEA DRM Version 2.0

4. FEA DRM Structure

5. Use DRM Context to: Performance Reference Model (PRM) • Map data to inputs and outputs that support Performance Outcomes • Map data to processes by Lines of Business • Map data to Service Components by information flows • Map data to the infrastructure to plan for interoperability • Inputs, Outputs, and Outcomes • Uniquely Tailored Performance Indicators Business Reference Model (BRM) • Lines of Business • Agencies, Customers, Partners Service Component Reference Model (SRM) • Service Domains, Service Types • Business and Service Components Technical Reference Model (TRM) • Service Component Interfaces, Interoperability • Technologies, Recommendations FEA Data Reference Model (DRM) relationship with Other FEA Reference Models The DRM relates to each of the other FEA Reference Models

6. Data Context: Figure out the Data that the Enterprise (aka Community of Interest) cares about. • Data Description: • Figure out the standards: • Standard Meanings • Standard Structures Data Sharing: Figure out the services required to share information The DRM Approach(Summary) • The DRM provides basic guidance on what to capture in each of these areas and how to capture it. (i.e., the Abstract Model) • Intentionally, the DRM does not delve into specific models or artifacts that the architects will create: • Organizations use different EA Frameworks. There are a lot of right ways. • The models/artifacts developed will depend on what’s needed • As we define best practices, we will consider more definitive guidance in the DRM • However, the objective is to provide actionable guidance to your programs: We should be building with data sharing in mind up front. - “Build to Share”

7. FEA DRM Abstract Model(Guidance for Organizing Information About Agency Data)

8. FEA DRM Three Pillar Data Strategy Framework

9. Business & Data Goals drive The Rule: All 3 pillars are required for an effective data strategy. Governance Data Strategy Information Sharing/Exchange (Services) Data Architecture (Structure) The DRM Data Strategy Framework Goals drive; governance controls; structure defines; and services enable data strategy. Special thanks to Laila Moretto and Forrest Snyder, MITRE Corp.

10. Inventory Discovery Data Oversight Definitions/Semantics Policy & Procedures Structure Communities of Interest Education/Training Syntax Search Processes and Practices Pedigree Data Registries Issue Resolution Authoritative Sources Data Catalogs Metrics/Incentives Security/Protection Data Shared Spaces Data Transfer Standards Access Services Brokering Mediation Data Strategy Framework Sample Elements Information Sharing/Exchange (Services) Data Architecture(Structure) Governance Use of specific elements depend on the goals

11. Oversight Policy & Procedures Education/Training Processes and Practices Metrics/Incentives Education/Training Inventory Discovery Data Definitions/Semantics Structure Syntax Pedigree Authoritative Sources Security/Protection Data Data Transfer Standards Communities of Interest Search Data Registries Data Catalogs Shared Spaces Access Services Brokering Mediation Sample Data Management Goals and the Sample Elements of a Data Strategy Governance Data Goals: Visible Accessible Institutionalized Data Architecture Understandable Trusted Interoperable Responsive Information Sharing

12. Mapping the Sample Elements of the Strategy Framework to the DRM Data Contextenables… Data Descriptioncaptures… Data Sharingguides…

13. Governance Overview

14. Federal CIO Council Organization Executive Committee Director, Administrator of the Office of e-Government (OMB) Chair, Deputy Director for Management (OMB) Vice Chair (Agency CIO) Architecture & Infrastructure Committee Workforce & Human Capital for IT Committee Best Practices Committee Emerging Technologies Subcommittee Governance Subcommittee Services Subcommittee The Federal Data Architecture Subcommittee is one of four subcommittees under the Architecture and Infrastructure Committee. Data Architecture Subcommittee

15. Governance Strategy • Federal Data Architecture Subcommittee (DAS) • Chartered by Federal CIO Council • 2 Co-chairs appointed by AIC • Membership Federal CIO representation • Various work groups • Vision:Engage communications in advancing the management of Federal data as a valued national assets that supports the business of the Federal Government. • Key FY06/FY07 Activities/Deliverables • 1. FEA DRM updates and revisions • 2. Implementation strategies, best practices, and success stories • Establish an authoritative knowledge center for Federal data- • related issues and opportunities

16. Business & Data Goals drive Governance Data Strategy Information Sharing/Exchange (Services) Data Architecture (Structure) Communities of Interest (COI) and Line of Business (LOB)Vision Each COI or LOB will implement the three pillar framework strategy and will focus on business requirements.

17. DRM Implementation Examples

18. E-Gov Initiative: Recreation One Stop

19. Data Goals drive Gover-nance Data Strategy (Services) (Structure) E-Gov Initiative:Recreation One Stop • One of the President’s E-Gov inter-agency Initiatives led by DOI • Requirements: • Share data among multiple Federal, State, Local and Commercial partners • Share data across multiple business lines • Data standards must be easily extensible to accommodate new requirements • Data sharing standards must be translated to a database and XML

20. Data Goals drive Gover-nance Data Strategy (Services) (Structure) E-Gov Initiative:Recreation One Stop(Challenge) Customers see too many sources for Federal recreation information.

21. Permit Organization Sale Location Vendor Geospatial- Location Financial-Transaction Person Postal- Location Recreation Area Recreation Facility Reservation (Blue = Shared Data Concept) Descriptive- Location Recreation Activity Data Goals Country State River Trail Event/Incident drive Gover-nance Data Strategy (Services) (Structure) E-Gov Initiative:Recreation One Stop Structure: High Percentage of Data Reuse Identified

22. Subject Area: RECREATION Information Class: RECREATION ACTIVITY Information Exchange Package: RECREATION ACTIVITY QUERY Data Object: DOI Conceptual Data Entities (Standardized) RECREATION-AREA CREATE TABLE RECAREA (RECAREA_ID CHAR(12) NOT NULL, RECAREA_NM VARCHAR(50) NOT NULL PRIMARY KEY (RECAREA_ID)); CREATE UNIQUE INDEX XPKRECAREA ON RECAREA ( RECAREA_ID ASC); CREATE TABLE RECAREA_ACT (RECAREA_ID CHAR(12) NOT NULL, RECAREA_ACT_CD CHAR(2) NOT NULL, RECAREA_ACT_DESC VARCHAR(240) NULL, RECAREA_ACT_FEE VARCHAR(240) NULL); CREATE UNIQUE INDEX XPKRECAREA_ACT ON RECAREA_ACT ( RECAREA_ID ASC, RECAREA_ACT_CD ASC); Data Property: DOI Conceptual Data Elements (Standardized) Physical Model Schema (RIDB) RECREATION-AREA DENTIFIER RECREATION-AREA-ACTIVITY RECREATION-AREA NAME RECREATION-AREA MAP URL TEXT Data Element Description RECREATION-AREA IDENTIFIER (FK) RECREATION-ACTIVITY TYPE CODE Data Representation: RECREATION-AREA-ACTIVITY DESCRIPTION TEXT RECREATION-AREA-ACTIVITY FEE DESCRIPTION TEXT XML Schema Data Goals METADATA REGISTRY/REPOSITORY Glossary of Metadata DOMAIN: RECREATION-ACTIVITY TYPE CODE <?xml version="1.0" ?> <xsd:Schema xmlns:xsd="http://www.w3.org/2001/XMLSchema"> <xs:element name="RecAreaActivity"> <xs:annotation> <xs:documentation>A recreational activity available at a Recreation Area. </xs:documentation> </xs:annotation> <xs:complexType> <xs:sequence> <xs:element name="RecAreaActivityType" type="xs:string"> <xs:annotation> <xs:documentation>The code that denotes a specific kind of Recreational Activity.</xs:documentation> </xs:annotation> </xs:element> drive A1|AIR-HANG GLIDING B1|BOATING-SAILING B2|BOATING-CANOEING B3|BOATING-KAYAKING C1|CAMPING-CAMP SITES C2|CAMPING-FREE SPACE H1|HIKING-TRAILS H2|HIKING-FREE RANGE S1|SWIMMING-LAKE, POND S2|SWIMMING-POOL REGISTRY ENTRY: RECREATION-ACTIVITY TYPE CODE DATA TYPE: CHARACTER LENGTH: 2 DEFINITION: The code that denotes a specific kind of Recreational Activity CLASS WORD: CODE Gover-nance Data Strategy (Services) (Structure) E-Gov Initiative:Recreation One Stop Services: RecML is based on standards described in Recreation ERD

23. Data Goals drive Gover-nance Data Strategy (Services) (Structure) E-Gov Initiative:Recreation One Stop Services: Information Sharing Result

24. Data Goals drive Gover-nance Data Strategy (Services) (Structure) E-Gov Initiative:Recreation One Stop(Governance) • COI is Federal Recreation providers • Recreation Executive Council • Members are deputy assistant secretary level (DOI, USDA, & DOD) • Provides strategic perspective • Provides adjudication • Recreation Managers Committee • Senior level Recreation managers • Sets priorities • Members include Smithsonian, DOT, and 16 other agencies • Various implementation groups • One group is responsible for the adoption of data standards • Another group stewards the data • Another group responsible for data implementation

25. Cross-Cutting Initiative: Continuity Communications Architecture (CCA)

26. Data Goals drive Gover-nance Data Strategy (Services) (Structure) Continuity Communications Architecture (CCA) • Objective • Provide a high-level architectural design which can be used by Federal Departments and Agencies (D/As) to ensure execution of their Mission Essential Functions (MEFs) during all circumstances (including disasters, terrorism, and war) and operational states (including ECG, COG, and COOP) • Scope • Address Federal Executive Branch (FEB), with planned extensions into States, for all MEFs

27. Operations/ Business • Environment/ Situation Infrastructure CCA MetamodelThree Major Components • Environment/Situation • The Scenarios under which the D/As must operate • Operations/Business • What the D/As must do in any given Scenario • Infrastructure • The facilities, communications systems, hardware/software, and other capabilities the D/As use to accomplish their priority missions

28. Data Goals drive Gover-nance Data Strategy (Services) (Structure) CCA Structure:Metamodel Relationships Scenarios PMEFs NEFs Drive Drive Other Orgs Define Reside at Perform Perform Effects Require/ Produce Other Functions D/As Perform Environment/Situation Enable Affect Reside at Require/Produce Use Information Content Services Geographic Locations Operations/Business Implement Described by Infrastructure Affect Information Representations Are Identified With Applications Process Exchanges Store Reside on Communications Security Restricts Connect Protects Computing/Storage Platforms Facilities Reside at

29. User-friendly “front-end” to organize and catalog “As-Is” data • Employs “pick lists” based on consistent terminology • Facilitates data loading and minimizes data entry errors • An integrated repository to store CCA information • D/As and PMEFs • Information Needs and Representations • Communications and Security Capabilities • Networks and Protocols CCA Toolset • Analytical Capabilities • Identify interoperability and compatibility gaps • Assess ability of D/As to accomplish PMEFs Data Goals drive Gover-nance • Provides reports and other “views” • Information exchange disconnects • Communications infrastructure deficiencies Data Strategy (Services) (Structure) CCA Analytical Toolset

30. CCA Analysis Data Goals drive Gover-nance Data Strategy (Services) (Structure) Sample PMEF Analysis Information Gaps Provides INPUT 1 D/A # 2 NEF P Supports INPUT1 Report PMEF INPUT 2 Secure Call O Does NOT produce INPUT 2 Inputs required to perform PMEF D/A # 3 D/A # 1

31. Data Goals drive Gover-nance Data Strategy (Services) (Structure) CCA Data Context • “Information” is Key • What “Information Content” do the D/As need to share to support their Mission Essential Functions? • Information Content standardized • Aligned to BRM Lines of Business/Subject Areas • Seven basic types of information exchanges • Requests for Information • Report of Facts or Statistics • Guidance • Direction • Advice or Recommendations • Request for Authority • Financial Transaction • Specific types of “Information Representations” associated with each • Imagery, Voice, E-mail, Database, Text, etc.

32. Agency Initiative: HUD

33. Data Goals drive Gover-nance Data Strategy (Services) (Structure) HUDSingle Family Integration • Project Mission: • Consolidate the functionality and data from • 35 legacy systems operating on multiple • platforms • written in multiple programming languages • into • a single integrated system • operating in a service-oriented J2EE and Oracle • environment.

34. Data Goals drive Gover-nance Data Strategy (Services) (Structure) HUDSingle Family Integration • Challenges • Complexity of Target Logical Data Model • - Functions being defined and refined • - Capture of institution knowledge • - Moving target • Challenges • Legacy Data System • - System Focused • - Data Duplication • - Data Quality Data that is not used ( obsolete ) Legacy System Data that is redundant Legacy System Target Data that has been decomposed Logical Data In the Target LDM Model Data elements – unknown ? Legacy System Data that has been normalized In the Target LDM

35. Registry consisting of Legacy System Architecture Target Architecture Data & Service Mapping Bi-directional Traceability Data Goals drive Gover-nance Data Strategy (Services) (Structure) HUDSingle Family Integration(Structure)

36. Data Goals drive Gover-nance Data Strategy (Services) (Structure) HUDSingle Family Integration(Governance) • Modeled after the HUD Data Control Board Charter • Members: • Legacy System Subject Matter Experts (SME) • Target Architecture Experts • Attendees: • SF Integration Team members and other HUD staff • Board approves final data migration plans

37. Data Goals drive Gover-nance Data Strategy (Services) (Structure) HUDSingle Family Integration(Information Exchange Services) • In early stage • Metadata Management • Oracle Middleware • Connecting Software Applications • Exchanging Data • Leverage SOA to streamline information lifecycle

38. Agency Initiative: EPA Central Data Exchange (CDX)

39. Data Goals drive Gover-nance Data Strategy (Services) (Structure) EPACentral Data Exchange / Exchange Network Vision • The States and EPA are committed to a partnership to: • Build locally and nationally accessible, cohesive and coherent environmental information systems that will • Ensure the public and regulators have access to the information needed to • document environmental performance, • understand environmental conditions, and • make sound decisions to ensure environmental protection.

40. Data Goals drive Gover-nance Data Strategy (Services) (Structure) EPACentral Data Exchange / Exchange Network(Requirements) • Service Oriented Architecture (SOA) Framework • Standards Based • Strong Extensible Security Model • Utilizes Shared Services and Components • Interoperates Across Platforms • XML Schema Based Exchanges • Developed from Data Standards • Reuses Shared Schema Components

41. Program Silo 1 Registries Program Data Repositories & Data Warehouses Analysis and Access Systems Front End Data Collection Systems Program Information Consumers Program Silo 2 Registries Program Data Repositories & Data Warehouses Front End Data Collection Systems Analysis and Access Systems Program Information Consumers Program Silo 3 Registries Program Data Repositories & Data Warehouses Front End Data Collection Systems Analysis and Access Systems Program Information Consumers Program Silo 4 Registries Policy Makers Program Data Repositories & Data Warehouses Industry Front End Data Collection Systems Analysis and Access Systems Program Information Consumers Program Silo 5 Unmanageable Complexity (>100 data flows with custom formats and processes Registries Program Data Repositories & Data Warehouses Front End Data Collection Systems Analysis and Access Systems Program Information Consumers States Program Silo 6 Registries Program Data Repositories & Data Warehouses Front End Data Collection Systems Analysis and Access Systems Program Information Consumers Legislators Program Silo 9 Registries Local Govt Program Data Repositories & Data Warehouses Analysis and Access Systems Front End Data Collection Systems Program Information Consumers Program Silo 7 Registries Program Silo 10 Registries Program Data Repositories & Data Warehouses Analysis and Access Systems Front End Data Collection Systems Program Information Consumers Front End Data Collection Systems Program Data Repositories & Data Warehouses Analysis and Access Systems Program Information Consumers Program Silo 8 Universities Registries Program Data Repositories & Data Warehouses Front End Data Collection Systems Analysis and Access Systems Program Information Consumers Citizens Program Silo 19 Registries Program Data Repositories & Data Warehouses Analysis and Access Systems Front End Data Collection Systems Program Information Consumers Tribes Program Silo 15 Program Silo 14 Program Silo 18 Program Silo 13 Program Silo 17 Program Silo 16 Program Silo 12 Registries Registries Registries Registries Registries Registries Registries Program Data Repositories & Data Warehouses Front End Data Collection Systems Front End Data Collection Systems Program Data Repositories & Data Warehouses Program Data Repositories & Data Warehouses Program Data Repositories & Data Warehouses Program Data Repositories & Data Warehouses Analysis and Access Systems Analysis and Access Systems Front End Data Collection Systems Front End Data Collection Systems Front End Data Collection Systems Program Data Repositories & Data Warehouses Analysis and Access Systems Analysis and Access Systems Analysis and Access Systems Front End Data Collection Systems Front End Data Collection Systems Program Data Repositories & Data Warehouses Analysis and Access Systems Analysis and Access Systems Program Information Consumers Program Information Consumers Program Information Consumers Program Information Consumers Program Information Consumers Program Information Consumers Program Information Consumers Program Silo 11 Registries Program Data Repositories & Data Warehouses Front End Data Collection Systems Analysis and Access Systems Program Information Consumers Program Silo 20 Registries Program Data Repositories & Data Warehouses Analysis and Access Systems Front End Data Collection Systems Program Information Consumers Data Goals drive Gover-nance Program Silo 50+ Registries Program Data Repositories & Data Warehouses Front End Data Collection Systems Analysis and Access Systems Program Information Consumers Data Strategy (Services) (Structure) EPAChallenge But increased reporting and data use led to more and more complexity

42. Policy Makers Industry States Legislators Local Govt Universities Citizens Tribes • Standards Driven Data Sharing, • (not just data delivery) Data Goals drive Gover-nance Data Strategy (Services) (Structure) EPASolution Exchange Network

43. Data Goals drive Gover-nance Data Strategy (Services) (Structure) EPAExchange Network Governance

44. EPA Central Data Exchange / Exchange Network(XML Schema Management) Data Goals drive Gover-nance Data Strategy (Services) (Structure)

45. EPAExchange Network Status Data Goals drive Gover-nance Data Strategy (Services) (Structure)

46. Data Goals drive Gover-nance Data Strategy (Services) (Structure) EPAExample Service Integration

47. Contact Info for Each Implementation Example • Recreation One Stop • Charlie Grymes • E-mail:charlie.grymes@ios.doi.gov • HUD – Single Family Integration • Beverly Hacker • E-mail: beverly_s._hacker@hud.gov • EPA – Central Data Exchange/Exchange Network • Mark Luttner • E-mail: luttner.mark@epa.gov • CCA • Gary Amato • E-mail: Gary.amato@dhs.gov

48. Future Directions

49. What’s Next • Working Toward Six Strategic Goals: • Improve decision making by citizens and government • Improve availability of government information and services to citizens • Improve communication among government entities and with citizens • Reduce cost of Government through re-use of quality data • Improve quality, visibility, discovery, accessibility of and confidence in available information

50. What’s Next Continued • Continue Work of Six DRM Work Groups • DRM Governance • DRM Communications and Outreach • DRM ERP Harmonization • PERSON Harmonization • DRM Best Practices • XML Interoperability