METACURATE-ML: Generalising the extraction of questionnaires to DDI-Lifecycle

The canonical source for most large scale surveys remains for the past and the foreseeable future the ‘paper’ version of the questionnaire as a PDF. These contain the essential information on the fielding of the survey, the questions asked including response options, ordering and the logic associated with filtering to create DDI-Lifecycle metadata. However, there is no standard layout and formatting in these source documents which limits the scalability of heuristic programming approaches on OCR’ed text.The presentation will outline an approach to creating DDI-Lifecycle from semi-structured text in social science questionnaires using a combination of text-layout large language models (LLMs) and knowledge graph construction approaches, including methods from digital signal processing.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-12-02
DOI
https://doi.org/10.5281/zenodo.18182865
Primary Topic
Computational and Text Analysis Methods
Type
article
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article

METACURATE-ML: Generalising the extraction of questionnaires to DDI-Lifecycle

Suparna De, Jon Johnson, Chandresh Pravin
Zenodo (CERN European Organization for Nuclear Research)
Computational and Text Analysis Methods
article

METACURATE-ML: Generalising the extraction of questionnaires to DDI-Lifecycle

Suparna De, Jon Johnson, Chandresh Pravin
article en

Abstract

The canonical source for most large scale surveys remains for the past and the foreseeable future the ‘paper’ version of the questionnaire as a PDF. These contain the essential information on the fielding of the survey, the questions asked including response options, ordering and the logic associated with filtering to create DDI-Lifecycle metadata. However, there is no standard layout and formatting in these source documents which limits the scalability of heuristic programming approaches on OCR’ed text.The presentation will outline an approach to creating DDI-Lifecycle from semi-structured text in social science questionnaires using a combination of text-layout large language models (LLMs) and knowledge graph construction approaches, including methods from digital signal processing.

Zenodo (CERN European Organization for Nuclear Research)
University of Surrey (GB)
Responsible consumption and production
Openalex Percentile: Top 18%
Computational and Text Analysis Methods
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METACURATE-ML: Generalising the extraction of questionnaires to DDI-Lifecycle — Suparna De, Jon Johnson, et al. · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS