Scanning Technology and Its Application in Ethiopia Yakob Mudesir Deputy Director General Central Statistical Agency of Ethiopia

Slides:



Advertisements
Similar presentations
MICS4 Data Processing Workshop Multiple Indicator Cluster Surveys Data Processing Workshop Overview of Data Processing System.
Advertisements

Data Capture Methods. In this topic, we will be looking at: Methods of data capture When it would be appropriate to use each method Advantages and disadvantages.
UNSD-ESCWA Regional Workshop on Census Data Processing in the ESCWA region: Contemporary technologies for data capture, methodology and practice of data.
AUTOMATIC DATA CAPTURE  a term to describe technologies which aim to immediately identify data with 100 percent accuracy.
Brief Overview of Data Processing of Afghanistan Household Listing, Pilot Census Results, Population and Housing Census and NRVA Survey Brief Overview.
The 8 th ECO National Focal Points on Economic Research and Statistics ( April 2011, Baku, Azerbaijan) Country Report of the I.R. Iran Statistical.
UNSD Census Workshop Day 2 - Session 6 Data Capture: Optical Mark Recognition Andy Tye – International Manager DRS are Worldwide specialists in data capture.
Census Data Capture Challenge Intelligent Document Capture Solution UNSD Workshop - Minsk Dec 2008 Amir Angel Director of Government Projects.
General Statistics Office of Vietnam THE 2009 VIETNAM POPULATION AND HOUSING CENSUS.
Data capture of the PHC 2002 (Uganda) Experiences and lessons leant.
UNSD Regional Workshop on Census Data Processing for the English speaking African Countries: Contemporary technologies for data capture, methodology and.
UNSD Census Workshop Day 2 - Session 6 Data Capture: Optical Mark Recognition Andy Tye – International Manager DRS are Worldwide specialists in Census.
Manual Data Processing of Census Data 2004 Population and Housing Census Statistics Sierra Leone Thekeka Moses Conteh Sierra Leone.
The Core Welfare Indicators Questionnaire: A CWIQ Option for Monitoring Poverty Reduction Strategies.
1 Use of scanning technology for data capture ICR System (Intelligent Character Recognition) Information and Communication Technology Center National Statistical.
OCR GCSE ICT DATA CAPTURE METHODS. LESSON OVERVIEW In this lesson you will learn about the various methods of capturing data.
1 Census 1996, 2001 & Community Survey (CS) United Nations Regional Workshop on Census Data Processing Contemporary Technology from Census Data Capturing.
By Cleophas Kiio Director, ICT 15-sep-101 The Best Practices in Census Data Processing Operation: Case of 2009 Census:
DRS Census Experience Andy Tye International Manager, DRS DRS Census Experience Andy Tye International Manager, DRS Census Meeting – New Caledonia Feb.
UNSD-ESCWA Regional Workshop on Census Data Processing in the ESCWA region: Contemporary technologies for data capture, methodology and practice of data.
Sterling Chadee Director of Statistics. The processing of the data from the field enumeration began in July 2011 until September All data processors.
Changing the culture: Ethiopia’s commitment to dissemination and the multi-media approach By Yakob Mudesir Seid
AS Module 2 Information; Management and Management and Manipulation or what to do with data, how to do it, and……... ensure it provides useful information.
UNSD Regional Workshop on Census Data Processing for the English speaking African Countries: Contemporary technologies for data capture, methodology and.
Regional Workshop on the 2010 World Programme on Population and Housing Censuses: International standards, contemporary technologies for census mapping.
IN THE MEANTIME…. INTERIM SOLUTIONS TO AUTOMATED DATA CAPTURE.
1 DATA CAPTURE – PROCESSING 2006 POPULATION & HOUSING CENSUS OF NIGERIA Presented at UN Regional Workshop on Census Data Processing By Adesola Fatilewa.
Using OCR for Census Data Capture in China National Bureau of Statistics of China.
Workshop on International Standards, Contemporary Technologies and Regional Cooperation, Noumea, New Caledonia, 04–08 February 2008 Results Generated from.
© CCI Learning Solutions Inc. 1 Lesson 5: Basic Troubleshooting Techniques Computer performance Care of the computer Working with hardware Basic maintenance.
© Beta Systems Software AG Process Stages of Census Surveys Richard J. Lang, International Manager September 2008, Bangkok.
Data Capture Overview United Nations Statistics Division
UNSD Census Workshop Day 2 - Session 7 Data Capture: Intelligent Character Recognition Andy Tye – International Manager DRS are Worldwide specialists in.
UNSD Regional Workshop on Census Data Processing for the English speaking African Countries: Contemporary technologies for data capture, methodology and.
Data Capture Understand the concept of data encoding. Describe methods of data capture and identify appropriate contexts for their.
European Conference on Quality in Official Statistics Session 26: Quality Issues in Census « Rome, 10 July 2008 « Quality Assurance and Control Programme.
Uganda – October 2009 Census Data Collection & Processing John Gomersall.
Copyright 2010, The World Bank Group. All Rights Reserved. ICT - a core management issue Part 1 Managing ICT resources Produced in Collaboration between.
Bharat Sharma Nepal POPULATION & HOUSING CENSUS OF NEPAL: AN EXPERIENCE OF OUTSOURCING REGIONAL WORKSHOP ON CENSUS DATA PROCESSING September, 2008.
Multi-modal of data collection for the 2010 Population and Housing Census National Statistical Office, Thailand (Daejeon, Republic of Korea, April.
Census Data Processing: Contemporary Technologies for Data Capture Bangkok, Thailand September, 2008 By Jatan Kumar Saha Systems Analyst Bangladesh.
Data Management Seminar, 9-12th July 2007, Hamburg 11 ICCS 2009 – Field Trial Survey Operations Overview.
Mazlan Sulong Department of Statistics MALAYSIA Census Data Capture MALAYSIA Population Census 2000 vs Population Census 2010 (proposed solution)
Statistical Expertise for Sound Decision Making Quality Assurance for Census Data Processing Jean-Michel Durr 28/1/20111Fourth meeting of the TCG - Lubjana.
1 BPS Statistics Indonesia New York, February 2011.
Data processing of the 1999 Vietnam Population Census.
Data Processing of the 2010 Population and Housing Census September 2008, Bangkok, Thailand National Statistical Office, Thailand.
UNSD-UNESCAP Regional Workshop on Census Data Processing: Contemporary technologies for data capture, methodology and practice of data editing, documentation.
Regional Workshop on the 2010 World Programme on Population and Housing Censuses: International standards, contemporary technologies for census mapping.
Regional Workshop on the 2010 World Programme on Population and Housing Censuses: International standards, contemporary technologies for census mapping.
Census Data Capture with OCR Technology: Ghana’s Experience Presented at the UNSD Regional Workshop on Census Data Processing Dar es Salaam, Tanzania 9.
Use of Mobile Technology for Data Collection in Zimbabwe Experiences Gained and Lessons Learnt By Rodgers M. Sango Zimbabwe National Statistics Agency.
United Nations Regional Workshop on the 2010 World Programme on Population and Housing Censuses: Census Evaluation and Post Enumeration Surveys, Asunción,
UNSD-ESCWA Regional Workshop on Census Data Processing in the ESCWA region: Contemporary technologies for data capture, methodology and practice of data.
UNSD-UNESCAP Regional Workshop on Census Data Processing: Contemporary technologies for data capture, methodology and practice of data editing, documentation.
Census Planning and Management
Standard Input Devices
UN Reg. Workshop on the 2020 World Programme on
UNSD Census Workshop Data Capture: Intelligent Character Recognition
Ethiopian 2007 CENSUS DATA CAPTURING AND PROCESSING
Post Enumeration Survey Census
OCR GCSE ICT Data capture methods.
Egypt’s Population, Housing & Establishments e-Census, 2017
Omenya Nyahul Kenya National Bureau of Statistics
Data Capture Process Stages
Data Capture - ICR Typical Workflow
POPULATION AND HOUSING
Optical Data Capture: Optical Mark Recognition (OMR)
Albania 2021 Population and Housing Census - Plans
Manual Data Capture – Key Entry
Presentation transcript:

Scanning Technology and Its Application in Ethiopia Yakob Mudesir Deputy Director General Central Statistical Agency of Ethiopia Web: October 2009 Kampala, Uganda

Outline: Background Scanning Technology Requirements for Scanning The Ethiopian Experience

 Population and Housing Census process is the largest data capturing exercise that a country can undertake.  It involves capturing of millions of forms  The Central Statistics Agency (CSA) started using old techniques like Punched Card Reader as early 1960’s.  Two Population and Housing Censuses have so far been conducted in Ethiopia using the traditional method of data capturing.  The first Population and Housing Census was carried out in Background

 During the 1984 Census:  Data capture was done on manual keyboard based entry using mainframe computer  FORMSPEC data entry system was used  It took more than 2 years to capture the data for about 42 million people.  In the case of the 1994 Census:  Data capture was again done on manual keyboard entry basis using PC’s  CENTRY data entry system (IMPS) was used Background

 It took about 18 months to capture the data for the population of about 53 million.  The entry work was done on 2-shift basis  About 180 data entry clerks were involved  Around 90 Pc’s were used Background

 Time consuming  Does not allow the availability of timely data  The data will be weaker in representing the current or existing situation  Subject to additional non-sampling errors  Human error due to manual keying  Due to the volume of the data, a 100% verification as in the case of sample surveys, is difficult. Some Limitations of the Keyboard Manual Entry Method

 Involves a great deal of human resource management.  Large number of data entry operators and equipment required Some Limitations of the Keyboard Manual Entry Method

The need to have the census result right on time and the limitations discussed above forced the statistical offices to look for other alternatives.. specially related to large volume of data - The Emerging of Scanning Technology The need for alternative solution

 The Scanning Technology in general implements two basic techniques  Mark recognition, like the Optical Mark Reader (OMR)  Character recognition, like the Optical Character Recognition (OCR) and the Intelligent Character Recognition (ICR) The Scanning Technology

 OMR is the recognition of shaded marks (blobs) on the forms  The positioning of these blobs on a form determines the alphanumeric characters they represent  The character recognition is the recognition of alphanumeric characters on forms and they are of 2 types:  OCR which is the recognition of machine printed characters and..  ICR which refers to the capture of hand- printed characters from a form The Scanning Technology

 Significant decrease in time required to capture the data  This helps to get timely data  Users’ need satisfied (policy makers, planners, researchers, etc.)  Reduces the non sampling error  No need to worry to store millions of forms for possible future references  Scanning captures the whole content of a questionnaire in an electronic image format Major Benefits of the Scanning Technology

EXPORTEXPORT Scanning Recognition & Extraction The Process involved in Scanning

- Proper planning - On the DESIGN of the questionnaire - On PRINTING the questionnaire - On RECORDING answer - On Questionnaire HANDLING - On securing ADEQUATE SPACE for questionnaire movement Why? In order to minimize the rejection rate and increase the Recognition Rate Requirements for Effective Scanning

 Proper training  Both on Hardware and Software  This helps to “ own” the technology  Being able to use the technology after the departure of the trainers / technical advisors  A well organized space for forms and data flow is required Requirements for Effective Scanning

- A Reliable Network System Requirements for Effective Scanning

Data Processing Center Warehouse Registering the EA Received from the Field Receiving Receiving the Questionnaires Registering the EA for Scanning Waiting Room Scanning Room Validation Room Processing Room Store A WELL STRUCTURED SPACE FOR FILE FLOW Requirements for Effective Scanning

File recorder: Records the ID of the outgoing questionnaires Filing Box handler Checks the village code on the box is the same as on the questionnaire Machine room box handler Checks the number, orientation and damage to questionnaires Guillotine Machine operator Cuts the binding edge off all questionnaires in the village in one operation and places them on the scanner Scanner technician Ensures smooth running of the machine and assists with the paper handling BO X Scanner Paper Handler Responsible for checking paper throughput through the scanner Computer operators (x2) Responsible detecting errors in the scanning process Stitching machine operator lifts paper off scanner and stitches in the bottom left corner Machine room box handler returns box to the File recorder Filing Box handler Returns the questioanires to the shelves File recorder: Records the ID No of the incomming questionnaires. Loos e Pap er Principal Supervisor Senior Supervisor Scanner Supervisor Proper File Management Requirements for Effective Scanning

 Proper file management and care  Checking batch (EA) IDs and orientation of forms  Proper recording of the in-coming and out- going questionnaires  Ensuring the EA code on each box is the same as the one on the questionnaires  Close attention in detecting errors in the scanning process is required Requirements for Effective Scanning

The Ethiopian Experience

 Study tour made in two African countries  Tanzania  To learn from their successes  Data capture of the 2002 Census of Tanzania was done in about 26 days  General report tables were produced within 3 months from the start of the scanning Experience Sharing

 Ghana  To learn from their difficulties  Data capture of the 2000 Census took about 6 months - ( forms from 29,000 EAs)  3 Scanners were used (Kodak, Fujitsu) > The larger scanner was Kodak 500D > Speed: About 500 forms/min  Power failure was one of the major problems > Loss of some data occurred as a result > A large generator was installed to minimize the effect of the frequent power cut Experience Sharing

Identification of the Technology  For scanning of the 2007 Census the Optical Mark Reader (OMR) technique was used  Scanning Technology to be used PhotoScribe Series PS900 Scanners DRS Scanning Technology product

DRS Photo Scribe Series PS900  High speed Imaging Mark Reader  Windows XP professional  Network connectivity  CD R/WR drive  A TFT monitor, Keyboard, mouse  Speed: up to 8,500 forms / hour Identification of the Technology

Design and Printing of Forms  Types of the 2007 Census forms  Short questionnaires  Long questionnaires  Household Listing Forms  Summary Forms  Community Level Forms  Batch Header Form – Scanned to create EA database

Long Questionnaire Design and Printing of Forms

Control Database Form Summary Form Design and Printing of Forms

 Data from the Pilot Census successfully scanned (OMR), key-corrected, exported to text format, tabulated and tested.  One scanner (PS 900 Photo Scribe) was used to capture the pilot data  Technical experts from the DRS company assisted in capturing, validating and exporting the pilot data Pilot

 Hardware and Software training  16 professionals trained  The training in general took about 7 working days  SOSKITW for Windows:- a DRS software package for scanning was used  Components of the SOSKITW Software :  SOSGen : - used to generate scanning decodes for completed OMR forms (How marks on forms are interpreted and stored)  SOSInp : - used to scan, validate and export scanned data. Training

 Equipment purchased and installed  10 additional PS900 iM2 DRS Scanners  16 high capacity PC’s for key-correction  Census data processing work plan prepared  Recruitment of temporary staff  Staff training (scanning technology, CSPro)  Retrieval and organization of completed forms  Scanning and validation  Computer editing and tabulation (For each activity: duration and responsible body are indicated) Preparatory Activities

 About 33 teams for registering and organizing forms are organized 3 persons assigned per team  Census data processing teams organized  Batch header database group  Scanning and validation team  Shift supervisors  Two senior programmers responsible for the overall scanning process  Other sub-professional staff assigned  4 batch header scanning technicians  16 data validation workers Preparatory Activities

–The scanning room organized – An air conditioner for the scanning room installed – A high capacity automatic generator installed to ensure uninterrupted power supply Preparatory Activities

 Organized forms taken from store to the waiting room  Batch header information printed and associated with its respective EA box  The existence of each EA verified  Checked EAs sent to the scanning room  Scanned forms are finally sent back to the stores  Scanned data are validated / key-corrected The Scanning Process

The actual scanning started mid July and the scanning work has been completed in November 2007 The Scanning Process

 Scanned, key-corrected and exported data  Batch Edit program based on edit specs provided by subject matter specialists developed and run on the data.  The software to be used in editing the data will be the Census and Survey Processing System (CSPro) Data Cleaning / Computer Editing

Owning the Technology Two Professionals have been trained in England for two weeks on scanned document processing using DocXP in close collaboration with DRS Printing of the Questionnaire locally Questionnaire design Our Professionals are working hard to process the upcoming welfare Monitoring Survey using scanning technology Future Plan

THANK YOU