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<p>Over the last twenty years, open data has developed into a&#xa0;central field of research that touches on a&#xa0;variety of scientific disciplines. By analyzing 13,538 scientific literature sources from the EBSCOhost database, the characteristics of this field of research are made transparent. Central topics, theoretical approaches, research methods used and development trends are identified. To achieve this, various methods and application systems were used to extract and analyze bibliographic data. The study shows that the research field of open data is characterized by a&#xa0;pronounced thematic and methodological diversity. Thematically, the research ranges from government transparency and economic applications to information technology innovations in the structuring and integration of open data sets. Theories from various disciplines are applied, with psychological and political science theories being used alongside theories from economics and computer science. Methodologically, both qualitative and quantitative approaches are used, ranging from case studies and experiments to prototype development. The literature analysis indicates that the research field of open data will be stimulated in the future by modern analysis methods—particularly from the field of generative AI.</p>

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Open Data im Spiegel der wissenschaftlichen Literatur – Eine quantitative Literaturanalyse von 2005–2024

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年6月25日

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  • Frank Bensberg,
  • Andreas Jede

摘要

Over the last twenty years, open data has developed into a central field of research that touches on a variety of scientific disciplines. By analyzing 13,538 scientific literature sources from the EBSCOhost database, the characteristics of this field of research are made transparent. Central topics, theoretical approaches, research methods used and development trends are identified. To achieve this, various methods and application systems were used to extract and analyze bibliographic data. The study shows that the research field of open data is characterized by a pronounced thematic and methodological diversity. Thematically, the research ranges from government transparency and economic applications to information technology innovations in the structuring and integration of open data sets. Theories from various disciplines are applied, with psychological and political science theories being used alongside theories from economics and computer science. Methodologically, both qualitative and quantitative approaches are used, ranging from case studies and experiments to prototype development. The literature analysis indicates that the research field of open data will be stimulated in the future by modern analysis methods—particularly from the field of generative AI.