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<p>Assessing the quality of research data is a&#xa0;crucial practice for the validity and integrity of research results. Only when data is accurate, consistent, and complete is it possible to draw correct conclusions about the subject of research. Despite its importance, data quality lacks a&#xa0;standardized platform for the social sciences that systematically collects, processes and demonstrates tools through use cases. To this end, the BMFTR-funded <i>Competence Center Data Quality in the Social Sciences</i> (KODAQS) is developing tools to better assess the quality of research data. In this article, the KODAQS tools are presented and explained conceptually. One focus will be on tools whose use cases are particularly relevant for communication and media studies. These represent a&#xa0;central resource that supports communication and social scientists in assessing and improving the quality of their research data. Tools for three types of data are presented: digital behavioral data, survey data, and linked data. These range from text preprocessing of social media data to the response qualities of multi-item scales in surveys and the comparison of different matching methods of survey and georeferenced data. All in all, the article should not only be understood as a&#xa0;mere presentation of the tools, but also as an impetus for more exchange of tools and workflows for ensuring high-quality research data.</p>

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Die KODAQS-Tools – Eine neue Ressource zur Beurteilung der Qualität von Forschungsdaten

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年4月15日

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  • Yannik Peters,
  • Fabienne Krämer,
  • Anne-Kathrin Stroppe,
  • Jun Sun,
  • Jessica Daikeler,
  • Çağla Yildiz,
  • Julian Dehne,
  • Henning Silber,
  • Stefan Jünger,
  • Katrin Weller,
  • Raniere Gaia Costa da Silva,
  • Beatrice Rammstedt,
  • Florian Keusch,
  • Frauke Kreuter

摘要

Assessing the quality of research data is a crucial practice for the validity and integrity of research results. Only when data is accurate, consistent, and complete is it possible to draw correct conclusions about the subject of research. Despite its importance, data quality lacks a standardized platform for the social sciences that systematically collects, processes and demonstrates tools through use cases. To this end, the BMFTR-funded Competence Center Data Quality in the Social Sciences (KODAQS) is developing tools to better assess the quality of research data. In this article, the KODAQS tools are presented and explained conceptually. One focus will be on tools whose use cases are particularly relevant for communication and media studies. These represent a central resource that supports communication and social scientists in assessing and improving the quality of their research data. Tools for three types of data are presented: digital behavioral data, survey data, and linked data. These range from text preprocessing of social media data to the response qualities of multi-item scales in surveys and the comparison of different matching methods of survey and georeferenced data. All in all, the article should not only be understood as a mere presentation of the tools, but also as an impetus for more exchange of tools and workflows for ensuring high-quality research data.