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<p>The aim of the study is to create a support methodology which by application of text analytical methods allow to improve meta-analysis of the project documentation. As a research object research documentation from Driving Urban Transition (DUT) partnership programme is used, ensuring that the insights gathered from ERA-NET Urban Accessibility and Connectivity (EN-UAC, 2023) projects are consistently used to identify the requirements of programme entities and help define future calls topics. Text mining techniques are applied to project documentation across different phases – proposals, first and second-year reports, and final reports – to identify similarities, gaps, and unique terms. The analysis highlights how these methods provide a better understanding of the project’s progression, the shifting focus, and compliance with DUT and Strategic Research and Innovation Agenda (SRIA) objectives. Methods such as word frequency analysis, TF-IDF scoring, and clustering allow for the identification of common themes and evolving priorities, helping ensure future projects align with overarching strategic goals. This approach enhances the efficiency of auditing documentation and supports better-informed decision-making for future project calls used by project evaluators and programme developers.</p>

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Applying Text Analytical Methodology to Audit the Project Documentation

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年8月28日

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  • Irina Arhipova,
  • Liga Paura,
  • Nikolajs Bumanis,
  • Gatis Vitols,
  • Vladimirs Salajevs,
  • Aldis Erglis,
  • Gundars Berzins,
  • Evija Ansonska

摘要

The aim of the study is to create a support methodology which by application of text analytical methods allow to improve meta-analysis of the project documentation. As a research object research documentation from Driving Urban Transition (DUT) partnership programme is used, ensuring that the insights gathered from ERA-NET Urban Accessibility and Connectivity (EN-UAC, 2023) projects are consistently used to identify the requirements of programme entities and help define future calls topics. Text mining techniques are applied to project documentation across different phases – proposals, first and second-year reports, and final reports – to identify similarities, gaps, and unique terms. The analysis highlights how these methods provide a better understanding of the project’s progression, the shifting focus, and compliance with DUT and Strategic Research and Innovation Agenda (SRIA) objectives. Methods such as word frequency analysis, TF-IDF scoring, and clustering allow for the identification of common themes and evolving priorities, helping ensure future projects align with overarching strategic goals. This approach enhances the efficiency of auditing documentation and supports better-informed decision-making for future project calls used by project evaluators and programme developers.