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Title:Validating science’s power players: scientometric mixed methods for data verification in identifying influential scientists in a genetics collaboration community
Author(s):Bratt, Sarah Elaine; Qin, Jian; Hemsley, Jeffrey Joe; Costa, Mark Raymond; Wang, Jun
Subject(s):cyber-infrastructure-enabled science
Scientometric data analytics
science of science policy
trace data validity
Abstract:The emergence of large international scientific data repositories has allowed cyber-enabled science a reflective look at itself through the lens of big scientometric analytics. Yet the drawbacks of using digital trace data from large social networks are well-documented. This poster reports the iterative process of interpreting complex network analysis (CNA) metrics of an international protein sequence data repository’s metadata (GenBank) to identify influential “power players” in the genomics community. We describe preliminary work in developing approaches for operationalizing the mapping of CNA measures to establish a gold standard for node influence, arguing for the necessity of a confirmatory feedback loop in informing data interpretation and science funding- and submission- policy. Concrete examples and network visualizations are presented to illustrate the challenges in identifying influential scientists using GenBank metadata.
Issue Date:2016-03-15
Citation Info:NA
Series/Report:IConference 2016 Proceedings
Genre:Conference Poster
Rights Information:Copyright 2016 is held by the authors. Copyright permissions, when appropriate, must be obtained directly from the authors.
Date Available in IDEALS:2016-03-08

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