Visualizing and Evaluating the Growth of Multi-Institutional Collaboration Based on Research Network Analysis

Research collaboration plays an important role in scientific productivity and academic innovation. Multi-institutional collaboration has become a vital approach for integrating multidisciplinary resources and expertise to enhance biomedical research. There is an increasing need for analyzing the eff...

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Main Authors:	Luo, Jake, Pelfrey, Clara, Zhang, Guo-Qiang
Format:	Online
Language:	English
Published:	American Medical Informatics Association 2014
Online Access:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4419767/

id	pubmed-4419767
recordtype	oai_dc
spelling	pubmed-44197672015-05-07 Visualizing and Evaluating the Growth of Multi-Institutional Collaboration Based on Research Network Analysis Luo, Jake Pelfrey, Clara Zhang, Guo-Qiang Articles Research collaboration plays an important role in scientific productivity and academic innovation. Multi-institutional collaboration has become a vital approach for integrating multidisciplinary resources and expertise to enhance biomedical research. There is an increasing need for analyzing the effect of multi-institutional research collaboration. In this paper, we present a collaboration analysis pipeline based on research networks constructed from publication co-authorship relationship. Such research networks can be effectively used to render and analyze large-scale institutional collaboration. The co-authorship networks of the Cleveland Clinical and Translational Science Collaborative (CTSC) were visualized and analyzed. SciVal Expert™ was used to extract publication data of the CTSC members. The network was presented in informative and aesthetically appealing diagrams using the open source visualization package Gephi. The analytic result demonstrates the effectiveness of our approach, and it also indicates the substantial growth of research collaboration among the CTSC members crossing its partner institutions. American Medical Informatics Association 2014-04-07 /pmc/articles/PMC4419767/ /pubmed/25954579 Text en ©2014 AMIA - All rights reserved. This is an Open Access article: verbatim copying and redistribution of this article are permitted in all media for any purpose
repository_type	Open Access Journal
institution_category	Foreign Institution
institution	US National Center for Biotechnology Information
building	NCBI PubMed
collection	Online Access
language	English
format	Online
author	Luo, Jake Pelfrey, Clara Zhang, Guo-Qiang
spellingShingle	Luo, Jake Pelfrey, Clara Zhang, Guo-Qiang Visualizing and Evaluating the Growth of Multi-Institutional Collaboration Based on Research Network Analysis
author_facet	Luo, Jake Pelfrey, Clara Zhang, Guo-Qiang
author_sort	Luo, Jake
title	Visualizing and Evaluating the Growth of Multi-Institutional Collaboration Based on Research Network Analysis
title_short	Visualizing and Evaluating the Growth of Multi-Institutional Collaboration Based on Research Network Analysis
title_full	Visualizing and Evaluating the Growth of Multi-Institutional Collaboration Based on Research Network Analysis
title_fullStr	Visualizing and Evaluating the Growth of Multi-Institutional Collaboration Based on Research Network Analysis
title_full_unstemmed	Visualizing and Evaluating the Growth of Multi-Institutional Collaboration Based on Research Network Analysis
title_sort	visualizing and evaluating the growth of multi-institutional collaboration based on research network analysis
description	Research collaboration plays an important role in scientific productivity and academic innovation. Multi-institutional collaboration has become a vital approach for integrating multidisciplinary resources and expertise to enhance biomedical research. There is an increasing need for analyzing the effect of multi-institutional research collaboration. In this paper, we present a collaboration analysis pipeline based on research networks constructed from publication co-authorship relationship. Such research networks can be effectively used to render and analyze large-scale institutional collaboration. The co-authorship networks of the Cleveland Clinical and Translational Science Collaborative (CTSC) were visualized and analyzed. SciVal Expert™ was used to extract publication data of the CTSC members. The network was presented in informative and aesthetically appealing diagrams using the open source visualization package Gephi. The analytic result demonstrates the effectiveness of our approach, and it also indicates the substantial growth of research collaboration among the CTSC members crossing its partner institutions.
publisher	American Medical Informatics Association
publishDate	2014
url	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4419767/
_version_	1613219192115298304

Visualizing and Evaluating the Growth of Multi-Institutional Collaboration Based on Research Network Analysis

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