Abstract
The advent of large data repositories and the necessity of distributed skillsets have led to a need to study the scientific collaboration network emerging around cyber-infrastructure-enabled repositories. To explore the impact of scientific collaboration and large-scale repositories in the field of genomics, we analyze coauthorship patterns in NCBIs big data repository GenBank using trace metadata from coauthorship of traditional publications and coauthorship of datasets. We demonstrate that using complex network analysis to explore both networks independently and jointly provides a much richer description of the community, and addresses some of the methodological concerns discussed in previous literature regarding the use of coauthorship data to study scientific collaboration.
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Notes
In an undirected network, these calculations should only be done for the upper or lower triangle, not both.
These totals differ slightly from 5 because datasets and publications with no dates are included in the figures.
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Acknowledgments
This research is sponsored by the NSF’s Science of Science Policy Program, Grant Number 1262535. The authors thank Jun Wang, Qianqian Chen for their technical assistance in data processing and analysis.
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Costa, M.R., Qin, J. & Bratt, S. Emergence of collaboration networks around large scale data repositories: a study of the genomics community using GenBank. Scientometrics 108, 21–40 (2016). https://doi.org/10.1007/s11192-016-1954-x
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DOI: https://doi.org/10.1007/s11192-016-1954-x