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.
Original language | English (US) |
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Pages (from-to) | 21-40 |
Number of pages | 20 |
Journal | Scientometrics |
Volume | 108 |
Issue number | 1 |
DOIs | |
State | Published - Jul 1 2016 |
Keywords
- Big data repository
- Complex network analysis
- Cyber-infrastructure enabled science
- Scientific collaboration
- Team science
ASJC Scopus subject areas
- General Social Sciences
- Computer Science Applications
- Library and Information Sciences