1961 Census Digitisation Project - Market Engagement - AWARD

The Office for National Statistics ('ONS') is responsible for running and producing results from the decennial census in England and Wales. This project is concerned with making greater use of historical census data.

1961 Census Small Area Statistics ('SAS') were produced as part of the aggregate statistical outputs from the 1961 Census. They contain more detailed information about population characteristics for much smaller areas than the main published outputs. The data are currently held in a set of more than 140,000 images of data in tables which were taken from microfilm generated from the original printed outputs.

In its current form the 1961 SAS data cannot be used for detailed analysis. Digitisation would 'unlock' the data, extending the census timeseries backwards with detailed and comparable socio-economic data. This would be welcomed by the research community and enable increased understanding of a period of rapid social change.

SCOPE

ONS want to convert the static 1961 SAS images into high quality statistical data in digital form that can be made available to users free of charge via an online portal with a file download facility. Previous exploratory work has proved that conversion into structured and operable data is possible and we are now keen to complete the digitisation work.

Our expectation is that the final digital data will be created in stages:

• oautomated extraction of data from the census volumes;
• oquality assurance to identify and correct any errors in the OCR outputs; and
• oa mechanism to assign missing values that cannot be extracted using OCR.

REQUIREMENTS

Subject to the number of expressions of interest and the successful evaluation and contract award, the service provider would require experience of handling, managing and facilitating access to historical census data, and a good knowledge of census geographies. A thorough understanding of quality issues in statistical data is essential.

ONS would also need evidence of a strong research background in document analysis and recognition, including expertise in the extraction of numerical information from tables. It is particularly important for numeric data that the extraction also includes metadata from the images.