TY - JOUR
T1 - The structural shift and collaboration capacity in GenBank Networks
T2 - A longitudinal study
AU - Qin, Jian
AU - Hemsley, Jeff
AU - Bratt, Sarah E.
N1 - Funding Information:
Research reported in this publication was supported by National Science Foundation Award No. 1561348 and the National Institute of General Medical Sciences of the National Institutes of Health under Award No. R01GM137409. The content is solely the responsibility of the authors and does not necessarily represent the official views of National Science Foundation and the National Institutes of Health.
Publisher Copyright:
© 2022 Jian Qin, Jeff Hemsley, and Sarah E. Bratt.
PY - 2022/4/12
Y1 - 2022/4/12
N2 - Metadata in scientific data repositories such as GenBank contain links between data submissions and related publications. As a new data source for studying collaboration networks, metadata in data repositories compensate for the limitations of publication-based research on collaboration networks. This paper reports the findings from a GenBank metadata analytics project. We used network science methods to uncover the structures and dynamics of GenBank collaboration networks from 1992–2018. The longitudinality and large scale of this data collection allowed us to unravel the evolution history of collaboration networks and identify the trend of flattening network structures over time and optimal assortative mixing range for enhancing collaboration capacity. By incorporating metadata from the data production stage with the publication stage, we uncovered new characteristics of collaboration networks as well as developed new metrics for assessing the effectiveness of enablers of collaboration—scientific and technical human capital, cyberinfrastructure, and science policy.
AB - Metadata in scientific data repositories such as GenBank contain links between data submissions and related publications. As a new data source for studying collaboration networks, metadata in data repositories compensate for the limitations of publication-based research on collaboration networks. This paper reports the findings from a GenBank metadata analytics project. We used network science methods to uncover the structures and dynamics of GenBank collaboration networks from 1992–2018. The longitudinality and large scale of this data collection allowed us to unravel the evolution history of collaboration networks and identify the trend of flattening network structures over time and optimal assortative mixing range for enhancing collaboration capacity. By incorporating metadata from the data production stage with the publication stage, we uncovered new characteristics of collaboration networks as well as developed new metrics for assessing the effectiveness of enablers of collaboration—scientific and technical human capital, cyberinfrastructure, and science policy.
KW - GenBank metadata analysis
KW - collaboration capacity
KW - collaboration networks
KW - impact assessment
KW - longitudinal study of collaboration networks
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U2 - 10.1162/qss_a_00181
DO - 10.1162/qss_a_00181
M3 - Article
AN - SCOPUS:85128399021
SN - 2641-3337
VL - 3
SP - 174
EP - 193
JO - Quantitative Science Studies
JF - Quantitative Science Studies
IS - 1
ER -