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

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

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

Underlying Theme Fully integrated information systems for a shared data environment

Fully integrated information systems for a shared data environment

Focus Information, Access, Authorization, Emerging Technologies Data Accessibility, Commonality, and Compatibility Design Data Dictionary Data Quality Security & Privacy Assurance

Information, Access, Authorization, Emerging Technologies

Data Accessibility, Commonality, and Compatibility Design

Data Dictionary

Data Quality

Security & Privacy Assurance

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

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

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!

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!

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

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

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

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 Primary Issues and Information Sharing Barriers 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 Stove-Piped Data Boundaries “ As Is State” Have Created HHS INDUSTRY Illustrative CDC DHS TSA USDA DOI ENERGY LABOR FDA INS Denotes data and information sets within agencies.

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

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 Subject Area Data Object Data Property Data Representation Data Classification

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

MODEL DRIVEN 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 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

The Structure META OBJECT FACILITY

The Tools

Federated Data Management Approach

The Result: Interagency Information Federation

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

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)

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

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

Leadership at DoD Decisions Processes

Decisions

Processes

Decisions “ Net-Centric Data Strategy & Communities of Interest (COI)”

Processes : The DoD Net-Centric Data Strategy aims at breaking down barriers to information sharing… 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 “ 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?” Organization “A” Organization “B” Organization “C” User is unaware this data exists User knows this data exists but cannot access it because of organizational and/or technical barriers ? 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 End-User Consumer End-User Producer

The Net-Centric Data Strategy is a key enabler of the Department’s transformation... The Strategy describes key goals to achieving net-centric data management… 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 (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 .

COIs are a key ‘implementer’ of data strategy goals… 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 COI Actions: Enable Data to be Trusted Enable Data Interoperability Make Data Accessible Enable Data to be Understandable Make Data Visible Key Goals

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