Building an Enterprise Architecture of Statistics Korea

Leechul Bae, Statistics Korea

Meeting on the MSIS, Daejeon, Korea, 26-29 April 2010

2Slide -

1. Back Ground

2. KOSTAT’s EA effort

3. Sharing Services Project with Government EA

4. Conclusion

Contents

3Slide -

Back Ground

Various Services & Information systems In 2009 Kostat be near completion of statistic

services by developing KOSIS, SGIS, MDSS etc• KOSIS : the world largest integrated DB of Macro data

at the nation level

• SGIS : a combination of statistics and maps

• MDSS : Microdata service, DW : Dataware House

Developing the Statistics Production System• Census System for population & business

• Integrated Administrative Data Management System

4Slide -

Back Ground

Still.. dissatisfactory Increased IT organization and expanded IT cost,

but still dissatisfaction• Because No governance system to control IT

There existed many problems• Each survey has respective survey system

• Duplicated application software without reuse

• Treat lightly standard of statistical information

To solve these Problem, New approach(EA) needed

5Slide -

KOSTAT’s EA effort

Vision & Strategies of the EA EA Vision

• To help building information system more efficiently

• To support the Production of high quality statistics

EA Strategies • Achievement-based support for business objectives

• Standardization and reuse of application systems

• Standardization of data and systematization of metadata management

• Reinforcement of the security system

6Slide -

KOSTAT’s EA effort

Four year’s Plan to Build EA(2008~2011)

The KOSTAT started building the EA at the CIO and CEO’s view in 2008 • In 2009 Building the EA at the designer’ view for

Population & Social Statistics Bureau

• In 2010 Building the EA at the designer’ view for application & data

• In 2011 Building the EA at the designer’ view for all perspective

Derived Improvement tasks• Improvement tasks for Statistical Business

• Improvement tasks for Informatization

7Slide -

KOSTAT’s EA effort

Improvement Plans for Statistical Business Standardize the statistical business process

• statistical business was optimized at the respective survey levels

• Standardization of the statistical production business was not sufficiently studied.

reinforcement of planning and analysis process• According to the comparison of GSBPM and the KOSTAT

statistical business process, the KOSTAT had a weakness for specify needs and evaluate process

• To solve this problem, the organizational restructuring for planning, analyses and services was suggested

8Slide -

KOSTAT’s EA effort

Social Statistics Planning Team

Social Statistics Analysis Team

Employment Statistics Division

Population Census Division

Vital Statistics Division

Welfare Statistics Division

Agriculture and Fisheries Statistics

DivisionAgriculture and

Fishery Production

Statistics Division

Social Statistics Service Team

GSBPM

KOSTAT process

Specify

needsDesign Build Collect

Process

Analyze

Disseminate

Archive

Evaluate

Planning ○

Preparation ○ ○ ○

Survey ` ○

Processing ○ ○

Data release ○ ○

Report and dissemination

○

Current organization

Comparison GSBPM and the KOSTAT Work Process

9Slide -

KOSTAT’s EA effort

The individual survey systems had much similarity in their functions

Improvement Plans for Information System

　Questi

on mgt.

Edit mgt.

Population mgt.

Sample mgt.

Enumeration district

mgt.

Enumerator mgt.

ED assignme

nt

Household register

mgt.

Questionnaire mgt.

Aggregation/

sampling

KOSIS uploadin

g

Microdata

transfer

Survey system

Household Wealth Survey System 　 ㅇ 　 　 ㅇ ㅇ ㅇ ㅇ ㅇ ㅇ ㅇ ㅇLocal Area Labor Force Survey System 　 ㅇ 　 　 ㅇ ㅇ ㅇ ㅇ ㅇ ㅇ ㅇ ㅇTime Use Survey System 　 ㅇ 　 　 ㅇ ㅇ ㅇ ㅇ ㅇ ㅇ ㅇ ㅇPrivate Education Expenditures Survey System 　 ㅇ 　 ㅇ ㅇ ㅇ ㅇ ㅇ ㅇ ㅇ ㅇ ㅇAgriculture and Fisheries Establishment Survey System 　 ㅇ 　 ㅇ ㅇ ㅇ ㅇ ㅇ ㅇ ㅇ ㅇ ㅇFarm Household Economy and Agricultural Production Cost Survey System

　 ㅇ 　 ㅇ ㅇ ㅇ ㅇ ㅇ ㅇ ㅇ ㅇ ㅇ

Fishery Production Survey System 　 ㅇ 　 ㅇ ㅇ ㅇ ㅇ ㅇ ㅇ ㅇ ㅇ ㅇAgriculture Survey System 　 ㅇ 　 　 ㅇ ㅇ ㅇ ㅇ ㅇ ㅇ ㅇ ㅇFisheries Survey System 　 ㅇ 　 　 ㅇ ㅇ ㅇ ㅇ ㅇ ㅇ ㅇ ㅇFood Grain Consumption Survey System 　 ㅇ 　 　 ㅇ ㅇ ㅇ ㅇ ㅇ ㅇ ㅇ ㅇIntegrated Household Management System ㅇ ㅇ 　 ㅇ ㅇ ㅇ ㅇ ㅇ ㅇ ㅇ ㅇ ㅇ Necessary to construct the generic statistics

production system to share and reuse application functions

10Slide -

KOSTAT’s EA effort

Generic National Statistics Management System

Generic Statistics Management System

Integrated administrative data management system

Integrated administrative data DB

Integrated national statistics Micro data management system

National statistics DW

< Needed to be built >< Currently is being built >

Integrated national statistics DB, (KOSIS)

Integrated national statistics DB

< Already built >

Website of statistical organizationsStartStart Process 1Process 1 Process nProcess n EndEnd

GSBPM (Generic Statistical Business Process Model)

Advanced statistical analysis tool (SAS, SPSS. etc)

Meta data management system

National statistics meta DB

E-survey system- Survey preparation, survey management, field survey and ICT support- Alternatives of field survey: CATI, CASI- Field survey support: PDA

< Currently is being built >

Statistical standards

Standards information

Statistical policy management system

Statistical coordination DB

< Needed to be advanced >

< Needed to be advanced >

Statistical geographic information system

Statistical GIS

< Needed to be advanced >

Population management system

Population DB

< Needed to be advanced >

11Slide -

Sharing Services with Government EA

EA of Korean government Ministry of Public Administration and Security

(MOPAS)charge of the EA of Korean government• MOPAS carry forward Sharing Project To avoiding the

duplication among agencies

• Among 38 domains of categorized Administrative services, 14 domains are presented the new target architecture to be improved.

Statistics management was diagnosed as diversification and advised to step up to the unification phase

12Slide -

Conclusion

The KOSTAT EA and the generic government EA greatly contributed to making the information planning of national statistics

necessary to introduce the EA plan proper for the situations of each agency. For this, related laws should be amended.

EA, terms should easy and convenient for the personnel of statistical production to understand and utilize. And the functions of the management system should be user-friendly