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

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.

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Publication Details

Journal
Scientific Data
Published
2025-12-02
DOI
https://doi.org/10.1038/s41597-025-06340-7
Primary Topic
scientometrics and bibliometrics research
Type
article
Field-Weighted Citation Impact
0.00

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article

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

Xiaowei Ma, Jiaxue Liu, Tkacheva NIu, Yuhong Qiu et al.
Scientific Data
scientometrics and bibliometrics research
article

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

Xiaowei Ma, Jiaxue Liu, Tkacheva NIu, Yuhong Qiu, Bo Yang, Hong Jiao
article en

Abstract

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.

Scientific DataVol. 13(1)
Nanjing Agricultural University (CN), Zhejiang Library (CN)
Government of Jiangsu Province, National Office for Philosophy and Social Sciences, Qinglan Project of Jiangsu Province of China
Openalex Percentile: Top 64%
scientometrics and bibliometrics research
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