28
Policy Awareness & Development in Information Technology Amit K. Maitra Executive Doctor of Management (EDM) Program, Case Western Reserve University Class of 2006

I T Evolution

Embed Size (px)

Citation preview

Page 1: I T  Evolution

Policy Awareness & Development in Information Technology

Amit K. MaitraExecutive Doctor of Management (EDM)

Program, Case Western Reserve UniversityClass of 2006

Page 2: I T  Evolution

Amit K. Maitra 2

CONTEXT

Global Environment Changing Technologies

NASA Space Station FREEDOM Program NASA Earth Observing Satellite Polar Ground Network

Innovations Transferable Information Exchange System (TIES)

Leadership Policy making Decisions Processes

Revolutionary moments Department of Homeland Security

Page 3: I T  Evolution

Amit K. Maitra 3

Underlying Theme

Fully integrated information systems for a shared data environment

Page 4: I T  Evolution

Amit K. Maitra 4

Focus

Information, Access, Authorization, Emerging Technologies Data Accessibility, Commonality, and

Compatibility Design Data Dictionary Data Locale Security & Privacy Assurance

Page 5: I T  Evolution

Amit K. Maitra 5

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

Page 6: I T  Evolution

Amit K. Maitra 6

Changing Technologies: NASA Space Station FREEDOM Program TMIS

International Partner Participation

Work Package Projects

Other Non-Work Package Centers

NSTS Office

30-Year Duration

Page 7: I T  Evolution

Amit K. Maitra 7

Changing Technologies: NASA Earth Observing Satellite Polar Ground Network

• Very complex, dynamic system accommodating SW growth and change, technology, and users● Data storage, processing, and transmissijon capacity

• Open system interconnection to provide data interchange between dissimilar elements within an open worldwide communication system● The network links various elements in the system – both the ground-based and space-borne components

Page 8: I T  Evolution

Amit K. Maitra 8

Innovations: Transferable Information Exchange System (TIES)

http://www.itu.int/members/index.html

Page 9: I T  Evolution

Amit K. Maitra 9

Leadership

• Policy Making• Decisions• Processes

Page 10: I T  Evolution

Amit K. Maitra 10

Policy Making

“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

Page 11: I T  Evolution

Amit K. Maitra 11

Decisions

“This Administration’s goal is to champion citizen-centered

electronic government that will result in a major improvement in the Federal government’s value to the citizen.” ~ The

President’s Management Agenda

Page 12: I T  Evolution

Amit K. Maitra 12

Business Reference Model (BRM)• Lines of Business• Agencies, Customers, Partners

Service Component Reference Model (SRM)

Technical Reference Model (TRM)

Busin

ess a

nd P

erfo

rmance

-Driv

en

Appro

ach

Performance Reference Model (PRM)

• Inputs, Outputs, and Outcomes• Uniquely Tailored Performance Indicators

.

Federal Enterprise Architecture (FEA)

• Service Domains, Service Types• Business and Service Components

• Service Component Interfaces, Interoperability• Technologies, Recommendations

Data and Information Reference Model (DRM)• Subject Areas, Classifications, Data Elements, • Data Properties, Data Representations

Inte

rop

era

bility

/ Info

rmatio

n S

harin

g(B

usin

ess-C

onte

xt D

riven

)

ProcessesThe Federal Enterprise Architecture (FEA) is a business and performance-based framework to

support cross-agency collaboration, transformation, and government-wide improvement

Page 13: I T  Evolution

Amit K. Maitra 13

Processes The Data and Information Reference Model, in particular, was created and validated in

partnership with several organizations, best practices, and leading practitioners

OMB Bob Haycock Department of Justice / GTRI Bob Greeves, Justice Industry Advisory Council (AIC) John Dodd XML Working Group Marion Royal, Co-Chair AIC Emerging Technologies Subcommittee Brand Niemann Logistics Management Institute (LMI) Mark Crawford Geospatial Community (GIS) Eliot Christian Health and Human Services (HHS) Melissa Chapman (CIO) Library Community Susan Tarr Records Management / NARA Reynold Cahoon US Patent and Trademark Office (PTO) Holly Higgins

Organizations, Practitioners:

Best Practices Followed / Leveraged:

ISO 11179 UN / CEFACT / ebXML Universal Business Language (UBL) OASIS / e-Gov Initiatives

Meta Object Facility (MOF) Resource Description Framework (RDF) W3C

Page 14: I T  Evolution

Amit K. Maitra 14

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 C

reate

d

HHS

INDUSTRY

Illustrative

Illustrative

CDC

DHS

TSA

USDA

DOI

ENERGY

LABOR

FDA INS

Denotes data and information sets within agencies.

Page 15: I T  Evolution

Amit K. Maitra 15

These inefficiencies have created enormous bottlenecks and problems in agencies’ ability to effectively describe, use, and share

information

Unclear knowledge of who to contact for specific data

Increased burden on finding and accessing the right data

Increased delays to satisfy citizen and stakeholder requests

Increasing costs to manage and integrate data

Increased corruption, sensitivity of data

Decreased ability to interoperate

Repeated new requests to collect the same data

Limited understanding of what data exists or where it is located

Has Le

d T

o

Stove-Piped Data Boundaries“As Is State”

Inefficiencies

Hard

er to

manag

e p

rivacy

/secu

rity issu

es

HHS

INDUSTRY

CDC

DHS

TSA

USDA

DOI

ENERGY

LABOR

FDA INS

Illus

trativ

eIllus

trativ

e

Denotes data and information sets within agencies.

Page 16: I T  Evolution

Amit K. Maitra 16

The Solution: The Data and Information Reference Model (DRM)

Subject Area

Data Object

DataProperty

DataRepresentation

DataClassification

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

Page 17: I T  Evolution

Amit K. Maitra 17

The DRM supports each of the other FEA Reference Models

Data and Information Reference Model (DRM)

Business Reference Model (BRM)• Lines of Business• Agencies, Customers, Partners

Service Component Reference Model (SRM)

Technical Reference Model (TRM)

Performance Reference Model (PRM)

• Inputs, Outputs, and Outcomes• Uniquely Tailored Performance Indicators

• Service Domains, Service Types• Business and Service Components

• Service Component Interfaces, Interoperability• Technologies, Recommendations

• Maps data to inputs and outputs that support Performance Outcomes

• Maps data to processes by Lines of Business

• Maps data to Service Components by information flows

• Maps data to the infrastructure to plan for interoperability

Page 18: I T  Evolution

Amit K. Maitra 18

... and “inner-connects” the FEA to provide a targeting framework to support the identification, integration, and implementation of cross-agency, cross-governmental information sharing initiatives

Health and Human Services (HHS)

(Federal Health Architecture)

States

Industry

DHS

FDA

CDC

PRM

BRM

SRM

TRM

DRM

Public Health Monitoring- Infectious Diseases-

Outbreaks reported by Public Health Authorities

Stockpiles, Research Data

Increased threats of bio-terrorism

Disease Outbreak Data

Adverse Event Reporting

Web Services Web Services

Federal Enterprise Architecture (FEA)

FEA Reference Models

Enterprise Architecture

Conceptual

Conceptual

Page 19: I T  Evolution

Amit K. Maitra 19

The DRM provides for increased business performance through efficiency gains by reducing the data burden for both the business manager and the technologist

Government-Wide Facilitates open / standard-based

interoperability Global identification of security and privacy

issues and solutions Supports electronic exchange and

interoperability of information Standards for Electronic Form design and

generation Facilitates electronic reporting, and G-to-G,

B, C interaction Categorization / integration of data along

functional lines of the business Provides clear data ownership and

stewardship

Agency-Specific Consolidated, standard data for Enterprise

Resource Planning Supports the discovery and use of existing

data components Increased efficiency in data storage and

access to/retrieval of data Facilitated implementation of GPEA and

PRA Compliant with OIRA requirements

Business Benefits Technical Benefits

Government-Wide Common data vocabulary and data

standardization to build integration adaptors and systems

Consistent means to categorize and classify data and information

Electronic registries and repositories for data components

Ability to create cross-agency, interoperable data architectures

Agency-Specific Facilitates the design of Target Enterprise

and Solution Architectures Controls for proper protection of data can

be defined Facilitated systems integration and

interoperability Re-use of data components as opposed to

duplication

ComplementaryBenefits

Page 20: I T  Evolution

Amit K. Maitra 20

What the DRM is, and what it isn’t…

A framework to support the classification of data and information in respect to how it supports the lines of business and functions within the BRM

A registry that provides multiple levels of granularity to satisfy the re-use of data schemas from multiple stakeholder views

A collection of interrelated (or woven), context-driven XML Schemas A framework that builds upon existing XML Schemas, Data Definition Libraries, and

initiatives that exist across the Government (e.g., UN/CEFACT, UBL, ISO 11179, OASIS, current e-Gov initiatives)

What it is:

What it isn’t: A government-wide data model, or entity relationship diagram (ERD) A replacement for ISO 11179 or other government-wide initiatives such as OASIS,

UN/CEFACT, UBL, ebXML, etc An all-encompassing mark-up language that describes the Federal Government (e.g., GOVML)

Page 21: I T  Evolution

Amit K. Maitra 21

BRM Function & Sub-Functions

DataClassification

Data Object

Data Property

Definition Ownership Stewardship(defines) (owns) (manages)*

Agencies/ISO* Agencies/ISO*

Agencies/ISO* Agencies/ISO*

FEA-PMO FEA-PMO FEA-PMO/AIC

AIC/AgenciesAIC/Industry/ Agencies/ISO

* Thousands of data elements have already been defined within ISO 11179 that the Federal Government can adopt / take advantage of

AIC/Agencies

Agencies/ISO*

Agencies/ISO*

Conceptual

Conceptual

DataRepresentati

on

Data Type

Value Domain(Namespaces)

ISO ISO ISO

Agencies/ISO*Agencies/ISO*Agencies/ISO*

Business Subject Area

FEA-PMO/Agencies Agencies Agencies

Responsibility for the creation and ongoing maintenance of the DRM, Subject Areas, Business Objects and Data Components /

Elements rests with various organizations...

Page 22: I T  Evolution

Amit K. Maitra 22

MODEL DRIVEN ARCHITECTUREMODEL 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

Revolutionary Moments: The Mandate

Page 23: I T  Evolution

Amit K. Maitra 23

The Structure

META OBJECT FACILITYMETA OBJECT FACILITY

Page 24: I T  Evolution

Amit K. Maitra 24

The Tools

Page 25: I T  Evolution

Amit K. Maitra 25

Department of Homeland Security and Federated Data Management Approach

Page 26: I T  Evolution

Amit K. Maitra 26

The Result: Interagency Information Federation

Page 27: I T  Evolution

Amit K. Maitra 27

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 ApproachBusiness & Performance Driven Approach

Page 28: I T  Evolution

Amit K. Maitra 28

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