文章基本信息

标题：A dataset of mentorship in bioscience with semantic and demographic estimations
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作者：Qing Ke ; Lizhen Liang ; Ying Ding 等
期刊名称：Scientific Data
电子版ISSN：2052-4463
出版年度：2022
卷号：9
期号：1
页码：1-12
DOI：10.1038/s41597-022-01578-x
语种：English
出版社：Nature Publishing Group
摘要：Mentorship in science is crucial for topic choice, career decisions, and the success of mentees and mentors. typically, researchers who study mentorship use article co-authorship and doctoral dissertation datasets . However, available datasets of this type focus on narrow selections of felds and miss out on early career and non-publication-related interactions. Here, we describe Mentorship, a crowdsourced dataset of 743176 mentorship relationships among 738989 scientists primarily in biosciences that avoids these shortcomings. Our dataset enriches the academic Family tree project by adding publication data from the Microsoft academic Graph and “semantic” representations of research using deep learning content analysis. Because gender and race have become critical dimensions when analyzing mentorship and disparities in science, we also provide estimations of these factors. We perform extensive validations of the profle– publication matching, semantic content, and demographic inferences, which mostly cover neuroscience and biomedical sciences. We anticipate this dataset will spur the study of mentorship in science and deepen our understanding of its role in scientists’ career outcomes.