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Leadership is evolving dynamically from an individual endeavor to shared efforts. This paper aims to advance our understanding of shared leadership in scientific teams. We define three kinds of leaders, junior (10–15), mid (15–20), and senior (20+) based on career age. By considering the combinations of any two leaders, we distinguish shared leadership as “heterogeneous” when leaders are in different age cohorts and “homogeneous” when leaders are in the same age cohort. Drawing on 1,845,351 CS, 254,039 Sociology, and 193,338 Business teams with two leaders in the OpenAlex dataset, we identify that heterogeneous shared leadership brings higher citation impact for teams than homogeneous shared leadership. Specifically, when junior leaders are paired with senior leaders, it significantly increases team citation ranking by 1–2 %, in comparison with two leaders of similar age. We explore the patterns between homogeneous leaders and heterogeneous leaders from team scale, expertise composition, and knowledge recency perspectives. Compared with homogeneous leaders, heterogeneous leaders are more impactful in large teams, have more diverse expertise, and trace both the newest and oldest references. 

Peer review is an important part of science, aimed at providing expert and objective assessment of a manuscript. Because of many factors, including time constraints, unique expertise needs, and deference, many journals ask authors to suggest peer reviewers for their own manuscript. Previous researchers have found differing effects about this practice that might be inconclusive due to sample sizes. In this article, we analyze the association between author-suggested reviewers and review invitation, review scores, acceptance rates, and subjective review quality using a large dataset of close to 8K manuscripts from 46K authors and 21K reviewers from the journal PLOS ONE’s Neuroscience section. We found that all-author-suggested review panels increase the chances of acceptance by 20 percent points vs all-editor-suggested panels while agreeing to review less often. While PLOS ONE has since ended the practice of asking for suggested reviewers, many others still use them and perhaps should consider the results presented here. 

Abstract 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 fields 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 profile–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. 

Scientific progress critically depends on disseminating analytic pipelines and datasets that make results reproducible and replicable. Increasingly, researchers make resources available for wider reuse and embed links to them in their published manuscripts. Previous research has shown that these resources become unavailable over time but the extent and causes of this problem in open access publications has not been explored well. By using 1.9 million articles from PubMed Open Access, we estimate that half of all resources become unavailable after 8 years. We find that the number of times a resource has been used, the international (int) and organization (org) domain suffixes, and the number of affiliations are positively related to resources being available. In contrast, we found that the length of the URL, Indian (in), European Union (eu), and Chinese (cn) domain suffixes, and abstract length are negatively related to resources being available. Our results contribute to our understanding of resource sharing in science and provide some guidance to solve resource decay. 

A dataset of mentorship in science. This is part of the article Ke, Q., Liang, L., Ding, Y. et al. A dataset of mentorship in bioscience with semantic and demographic estimations. Sci Data 9, 467 (2022). https://doi.org/10.1038/s41597-022-01578-x