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Statistical Quality Standard C1: Capturing Data

Purpose: The purpose of this standard is to ensure that methods are established and implemented to promote the accurate capture and conversion of paper forms or image files into data files for further processing.

Scope: The Census Bureau’s statistical quality standards apply to all information products released by the Census Bureau and the activities that generate those products, including products released to the public, sponsors, joint partners, or other customers. All Census Bureau employees and Special Sworn Status (SSS) individuals must comply with these standards; this includes contractors and other individuals who receive Census Bureau funding to develop and release Census Bureau information products.

In particular, this standard applies to the development, modification, and implementation of post-collection data capture operations, such as:

  • Operations to convert data on paper forms or maps into data files (e.g., key from paper (KFP) data entry, optical mark recognition (OMR), and optical character recognition (OCR)).
  • Operations to convert image files (e.g., fax image files received directly from respondents and geographic image files) into data files (e.g., key from image (KFI) data entry, the Economic Programs’ Paperless Fax Imaging Retrieval System (PFIRS), and operations to convert geographic image files into data files).

In addition to the global exclusions listed in the Preface, this standard does not apply to:

  • Electronic data collections (e.g., CATI, CAPI, and the Web). Statistical Quality Standard A2, Developing a Data Collection Instrument, addresses data capture performed within an instrument during data collection.

Key Terms: Data capture, key from image (KFI), key from paper (KFP), optical character recognition (OCR), and optical mark recognition (OMR).

Requirement C1-1: Throughout all processes associated with data capture, unauthorized release of protected information or administratively restricted information must be prevented by following federal laws (e.g., Title 13, Title 15, and Title 26), Census Bureau policies (e.g., Data Stewardship Policies), and additional provisions governing the use of the data (e.g., as may be specified in a memorandum of understanding or data-use agreement). (See Statistical Quality Standard S1, Protecting Confidentiality.)

Requirement C1-2: A plan must be developed that addresses:

  1. Requirements for the data capture systems.
  2. Required accuracy levels for data capture.
  3. Verification and testing of the data capture systems.
  4. Training for the staff who perform the data capture operations (including SSS contractors).
  5. Monitoring and evaluation of the quality of the data capture operations.

    Note: Statistical Quality Standard A1, Planning a Data Program, addresses overall planning requirements, including estimates of schedule and costs.

Requirement C1-3: Data collected on paper forms or in image files must be converted accurately into an electronic format suitable for subsequent processing.

Sub-Requirement C1-3.1: Specifications and procedures for the data capture operations must be developed and implemented.

Examples of activities that specifications and procedures might address include:

  • KFP data entry.
  • Scanning systems for paper forms and maps (e.g., OMR and OCR).
  • Operations to convert image files (e.g., fax image files and geographic image files) into data files (e.g., KFI data entry and PFIRS).

Sub-Requirement C1-3.2: Data capture systems and procedures must be verified and tested to ensure that all components function as intended.

Examples of verification and testing activities include:

  • Verifying that data capture specifications reflect the system requirements.
  • Verifying that data capture systems and software adhere to the specifications.
  • Verifying that data capture systems and software capture data accurately.

Sub-Requirement C1-3.3: Training for the staff (including SSS contractors) who perform the data capture operations (as identified during planning) must be developed and provided.

Sub-Requirement C1-3.4: Systems and procedures must be developed and implemented to monitor and evaluate the quality of the data capture operations and to take corrective actions if problems are identified.

Examples of monitoring and evaluation activities include:

  • Monitoring captured data (keyed or captured through an automated system) to ensure that it meets the specified accuracy requirements.
  • Monitoring and documenting the frequency and types of errors.
  • Taking corrective actions when data do not meet accuracy requirements (e.g., rejecting and repairing unacceptable batches, retraining key-entry staff, and adjusting automated systems and retesting).

Requirement C1-4: Documentation needed to replicate and evaluate the data capture operations must be produced. The documentation must be retained, consistent with applicable policies and data-use agreements, and must be made available to Census Bureau employees who need it to carry out their work. (See Statistical Quality Standard S2, Managing Data and Documents.)

Examples of documentation include:

  • Plans, requirements, specifications, and procedures for the data capture system.
  • Problems encountered and solutions implemented during the data capture operations.
  • Quality measures from monitoring and evaluating the data capture operations (e.g., error rates). (See Statistical Quality Standard D3, Producing Measures and Indicators of Nonsampling Error.)


  1. The documentation must be released on request to external users, unless the information is subject to legal protections or administrative restrictions that would preclude its release. (See Data Stewardship Policy DS007, Information Security Management Program.)
  2. Statistical Quality Standard F2, Providing Documentation to Support Transparency in Information Products, contains specific requirements about documentation that must be readily accessible to the public to ensure transparency of information products released by the Census Bureau.

Page Last Revised - October 8, 2021
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