North-south scientific collaborations on research datasets: a longitudinal analysis of the division of labor on genomic datasets (1992-2021).
North-south scientific collaborations on research datasets: a longitudinal analysis of the division of labor on genomic datasets (1992-2021).
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DOI：
10.3389/fdata.2023.1054655
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发表时间：
2023
影响因子：
3.1
通讯作者：
Nanoti, Abhishek
中科院分区：
文献类型：
--
作者：
Bratt, Sarah;Langalia, Mrudang;Nanoti, Abhishek
来自全球北方和南方的科学家之间的合作（南北合作）是“第四科学范式”的关键驱动力，并已被证明对应对COVID-19和气候变化等全球危机至关重要。然而，尽管他们的关键作用，N-S数据集上的合作并没有得到很好的理解。科学的科学研究往往依赖于出版物和专利来检查N-S合作模式。为此，全球危机的兴起需要南北协作来产生和共享数据，这迫切需要了解南北协作在研究数据集上的流行、动态和政治经济学。本文采用混合方法案例研究的方法，分析了29年（1992-2021年）提交给GenBank的数据集的南北合作的频率和分工。我们发现：（1）在29年的时间里，南北合作的代表性很低。当它们确实发生时，N-S合作显示出“突发性”模式，这表明N-S在数据集上的合作是在全球健康危机（如传染病爆发）之后反应性地形成和维持的;（2）数据集和出版物之间的分工在早期与全球南方不成比例，但在2003年之后变得更加重叠。科技能力较低但收入高的国家例外，这些国家在数据集上的普及率较高（例如，阿拉伯联合酋长国）。我们定性地检查了N-S数据集合作的样本，以确定数据集和出版物作者的领导模式。研究结果使我们认为，有必要将N-S数据集合作纳入研究成果的衡量标准，以微调N-S合作中公平性的当前模型和评估工具。该论文有助于实现SGD的目标，即开发数据驱动的指标，为研究数据集的科学合作提供信息。
Collaborations between scientists from the global north and global south (N-S collaborations) are a key driver of the “fourth paradigm of science” and have proven crucial to addressing global crises like COVID-19 and climate change. However, despite their critical role, N-S collaborations on datasets are not well understood. Science of science studies tend to rely on publications and patents to examine N-S collaboration patterns. To this end, the rise of global crises requiring N-S collaborations to produce and share data presents an urgent need to understand the prevalence, dynamics, and political economy of N-S collaborations on research datasets. In this paper, we employ a mixed methods case study research approach to analyze the frequency of and division of labor in N-S collaborations on datasets submitted to GenBank over 29 years (1992–2021). We find: (1) there is a low representation of N-S collaborations over the 29-year period. When they do occur, N-S collaborations display “burstiness” patterns, suggesting that N-S collaborations on datasets are formed and maintained reactively in the wake of global health crises such as infectious disease outbreaks; (2) The division of labor between datasets and publications is disproportionate to the global south in the early years, but becomes more overlapping after 2003. An exception in the case of countries with lower S&T capacity but high income, where these countries have a higher prevalence on datasets (e.g., United Arab Emirates). We qualitatively inspect a sample of N-S dataset collaborations to identify leadership patterns in dataset and publication authorship. The findings lead us to argue there is a need to include N-S dataset collaborations in measures of research outputs to nuance the current models and assessment tools of equity in N-S collaborations. The paper contributes to the SGDs objectives to develop data-driven metrics that can inform scientific collaborations on research datasets.
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影响因子：
14.9
作者：
Benson DA;Cavanaugh M;Clark K;Karsch-Mizrachi I;Ostell J;Pruitt KD;Sayers EW
通讯作者：
Sayers EW
影响因子：
29.9
作者：
Gomez, Charles J.;Herman, Andrew C.;Parigi, Paolo
通讯作者：
Parigi, Paolo
影响因子：
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作者：
Herzig Van Wees, Sibylle L.;Malqvist, Mats;Irwin, Rachel
通讯作者：
Irwin, Rachel
影响因子：
3.7
作者：
Faure MC;Munung NS;Ntusi NAB;Pratt B;de Vries J
通讯作者：
de Vries J
影响因子：
3.5
作者：
Haythornthwaite, C
通讯作者：
Haythornthwaite, C