Use Case: Archive Digitisation

Institute of Educational Science: Enabling New Insights with the Help of Intelligent Character Recognition (ICR)

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Overview

 A total of 12'200 handwritten survey forms contain information on the number of apprenticeship-leave examinations conducted and passed, expected apprenticeship leavers, and details of the contracts per canton in the respective survey year. Furthermore, these data sets contain important information for the history of education, and, the economy.

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Task

Information extraction from statistical survey forms from 1935-1969.

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Scope

12’200 handwritten forms

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Services
ICR (Intelligent Character Recognition), data extraction and the setup of a web editor.
"Acodis' editor is specific to our needs and allows for easy and efficient review and, if necessary, correction of the extracted data and metadata."
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Stefan Kessler, Operational Project Management "Education in Numbers"

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Starting Point

As part of the research project "Education in Numbers", the Institute of Educational Sciences at the University of Zurich analysed survey forms from the years 1935 to 1969 from the apprenticeship contract statistics of the former Federal Office for Industry, Trade and Labour. The forms contain information on the number of completed apprenticeship-leave examinations, expected apprenticeship leavers, details on apprenticeship contracts per respective canton and much more. The data set is of great importance for educational and economic history, among other things, but the documents were only available in physical and handwritten form.

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Our Approach

As an expert in the field of intelligent document processing (IDP), Acodis was commissioned to carry out the information extraction of the statistical survey forms.

At the beginning, a total of 12,200 survey forms were manually photographed and transmitted. The forms had five different layouts and, depending on the year, there were also differences in the handwriting. In order to be able to reproduce the information digitally, "Intelligent Character Recognition" was used, which enables the extraction of handwritten data.

In order to simplify the validation of the extracted values, a web editor was developed which allows the export into any data format. The structure, as well as the use, are easy to understand and do not require a long training period.

Customer Benefits

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State-of-the-Art Digitisation Tools

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Intuitive & Simple Data Validation
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Enabling New Research Results

Outcome

Thanks to the automated digitization solution, the project team saved countless working hours that would have been needed for manual document processing. In addition, all information of great interest for future research could be made available in digital form.

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