Any conclusions expressed herein are those of the authors and do 

not reflect the views of the U.S. Census Bureau. All results were 

approved for release by the Disclosure Review Board of the U.S. 

Census Bureau (Data Management System number: DMS P-7532197, 

Disclosure Review Board (DRB) approval numbers: CBDRB-FY24-

ERD006-001.

Digitization and 

Capture as a Service

October 26, 2023

2023 Federal Committee on Statistical Methodology (FCSM)

Research and Policy Conference

University of Maryland, College Park, MD.

Nevada Basdeo

Kevin Schweickhardt

Brandon Dubbs

U.S. Census Bureau
June 30, 2024

2
Why Transition to Electronic Records?

Challenges of Non-Digitial Physical Records

• Limited accessibility and 

inefficient retrieval

• Integration challenges and lack 

of security measures

• Data analysis inefficiency and 

collaboration hurdles

• Vulnerability to damage and 

deterioration

• Space requirements and backup 

limitations

• Mobility and version control 

issues

3
Decennial Census Digitization and Linkage (DCDL)

 Final component of creating longitudinal datasets that covers most of the U.S. population since 

1940

 Demonstrates the infrastructure and methodology required to digitize historical records 

and capture data

4

Methodology:

1. Scan microfilm reels from 1960-1990 Censuses and create digital images

2. Use Optical Character Recognition (OCR) and Optical Mark Recognition (OMR) to capture 

names and additional information

3. Link new information to already digitized data
5

The Census Bureau’s Secure Scanning Facility

National Processing Center (NPC)

Skilled scanning operations staff, cleared and badged for 

secure records handling

Production keying from image capabilities

High volume production scanning equipment Conversion of documents, books, microfilm and microfiche 

into digital images. 

Secure shipment, handling, and storage

Adherence to federal information security standards
6

High Level 

Flowchart for 

Digitization and 

Capture

Start

Data Finish

Records 

Assessment Secured Shipment Scanning Indexing & Metadata Quality Control

Text Localization Preprocessing Cloud Storage Character 

Recognition

Word and Text 

Formation Postprocessing

Cloud Storage E-Record Delivery

Capture: OCR (shown) & OMR

Digitization: National Processing Center

(secured government scanning facility)
Open-Source

Closed-Source 

Open-Source

Intricate and Complex Scenarios

• Ability to meet specific data capture 

requirements

• Can be extremely accurate

• Lengthy development and testing 

Moderately Complex Scenarios

• Can be highly accurate on complicated forms

• Accelerated deployment, lots of features

• Ease of use and maintenance

• Method is a black box (proprietary)

• Can be costly (per page structure)

General use cases

• Can meet straightforward requirements

• Requires fine tuning; to accommodate specific needs

• Performs well for less complicated forms

• Quick to moderate development time 

• Cost friendly

Tier System

Tailored approach to meet diverse 

needs, offering three tiers of solutions. 

The first or base tier is designed for 

straightforward requirements, while 

the third or top tier address the most 

intricate and complex data scenarios.

3 Classes of Models

CustomTrained

Pre-Trained

Pre-Trained
Open Source Pre

-

Trained (EasyOCR) • Flexible • Requires fine tuning • Can accommodate specific needs • Can be highly accurate on complicated forms • Segmented text when using “out-of-box” 

8
Open Source PreTrained (PaddleOCR)

• Flexible

• Requires fine tuning

• Can accommodate specific needs

• Can be highly accurate on 

complicated forms

• But can miss some information when 

using “out-of-box” 

9
Closed Source PreTrained (Textract)

• Can be highly accurate on 

complicated forms

• Accelerated deployment, lots of 

features

• Ease of use and maintenance

• Method is a black box (proprietary)

• Can be costly (per page structure)

10
Custom-Trained OCR Model (DCDL)

Name Mean Match Rate (SE)

First 0.91 (0.28)

Last 0.89 (0.32)

Middle 0.88 (0.33)

Suffix 0.94 (0.24)

1990 Mean Exact Word Match (N = 9,700)

All results were approved for release by the U.S. Census Bureau, Data 

Management System number: DMS P-7532197 and approval number CBDRBFY24-ERD006-001.

11
Custom-Trained OMR Model (DCDL)

OMR Marked 

Type 1*

OMR Marked 

Type 2*

Sample Size 541,000 533,000

Sample Pct 2.83% 0.15%

Percent Correct 98.66% 99.52%

Margin of Error 0.04% 0.02%

Lower CI 98.83% 99.50%

Upper CI 98.90% 99.55%

12

* Type 1 refers to empty bubbles and Type 2 refers to bubbles with numbers in it.

OMR Accuracy

All results were approved for release by the U.S. Census Bureau, Data Management 

System number: DMS P-7532197 and approval number CBDRB-FY24-ERD006-001.
Pre-trained and custom solutions to provide digital 

image data capture with a tiered and tailored 

approach to meet diverse needs

DCaaS Capture

Converting physical analog records 

(paper, microfilm, and microfiche) to digital 

records using federal digitization infrastructure 

capabilities

DCaaS Digitization

Methodology to digitize and capture microdata 

files from the 1960 – 1990 decennial census

Decennial Census Digitization and Linkage 

(DCDL)

M-19-21 and M-23-07 specifying the federal 

transition to electronic records

OMB & NARA Memorandums

Securely transforming physical records into digital data, 

ensuring compliance with federal regulations, and enabling 

efficient use of valuable information.

“Making Non-Digital, 

Digtial”

Digitization and Capture as a 

Service (DCaaS)

13

Facilitating the Transition to Electronic Records for 

Federal Agencies
The Census Bureau DCaaS Team

14

Thank you for attending our presentation. Please feel free to reach out to the DCaaS team, we are 

happy to meet, to discuss digitization & capture challenges and solutions including your agency’s 

electronic records, digitization and capture experience.

Nevada Basdeo

Program Director for Data Digitization

Business Development Staff

Economic Reimbursable Surveys Division

U.S. Census Bureau

nevada.basdeo@census.gov

301.763.7943

Kevin Schweickhardt

Data Digitization Program

Business Development Staff

Economic Reimbursable Surveys Division

U.S. Census Bureau - Contractor

kevin.l.schweickhardt@census.gov

301-763-5267

Brandon Dubbs

Data Digitization Program

Business Development Staff

Economic Reimbursable Surveys Division

U.S. Census Bureau - Contractor

brandon.m.dubbs@census.gov

301-763-0640