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<p>Scientific data has become a cornerstone of contemporary biomedical research, yet the academic recognition of data contributions remains underexplored. In this study, we leveraged the open-access biomedical literature in the PMC (PubMed Central) to identify GEO (Gene Expression Omnibus) datasets and extract their associated original papers. By examining the authorship relationships between dataset contributors and paper authors, we quantitatively assessed the academic recognition of scientific data. Our findings reveal that approximately 80% of dataset contributors play pivotal roles in their respective original papers, either as first or corresponding authors, with this proportion continuing to rise. This trend highlights the growing importance of data collection, processing, and analysis in the research process, along with its increasing recognition by the scientific community. Furthermore, we observed that high-impact journals invest more resources in enhancing data quality, thereby improving research credibility, academic influence, and overall research outcomes. These results underscore the gradual shift toward recognizing the value of scientific data work, which is critical for advancing research quality.</p>

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How does academia recognize the contribution of scientific data? Evidence from data contributors’ authorship

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年12月2日

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  • Jiaxue Liu,
  • Xiaowei Ma,
  • Hong Jiao,
  • Yuhong Qiu,
  • Tong Niu,
  • Bo Yang

摘要

Scientific data has become a cornerstone of contemporary biomedical research, yet the academic recognition of data contributions remains underexplored. In this study, we leveraged the open-access biomedical literature in the PMC (PubMed Central) to identify GEO (Gene Expression Omnibus) datasets and extract their associated original papers. By examining the authorship relationships between dataset contributors and paper authors, we quantitatively assessed the academic recognition of scientific data. Our findings reveal that approximately 80% of dataset contributors play pivotal roles in their respective original papers, either as first or corresponding authors, with this proportion continuing to rise. This trend highlights the growing importance of data collection, processing, and analysis in the research process, along with its increasing recognition by the scientific community. Furthermore, we observed that high-impact journals invest more resources in enhancing data quality, thereby improving research credibility, academic influence, and overall research outcomes. These results underscore the gradual shift toward recognizing the value of scientific data work, which is critical for advancing research quality.