JOURNAL ARTICLE

Visualizing co-authorship networks for actionable insights

Abstract

Increasing interest has been expressed in lowering the barrier for research access. Several approaches exist, including more active communication on research, the use of social computing-oriented networking tools for researchers, parallel publishing of research publications, and the use of research management systems for collecting, managing, and publishing bibliographical data. In this paper, we target the first step of research access, namely the use of publication metadata available in current research information systems. More specifically, we will take an action design research approach to experiment how visual network analytics could be used to create additional value for bibliographical data. We will tap into the current research information system of a selected university to develop a prototype of a self-service co-authorship network visualization and engage with four researchers to identify the key requirements for taking such an approach and to explore the potential value that could be created with visual analytics of bibliographical data. We contribute a set of design guidelines to support the development of computational visual network analytics tools for research collaboration analyses using bibliographical data.

Keywords:
Metadata Computer science Visual analytics Data science Cultural analytics Analytics Data publishing Visualization Set (abstract data type) World Wide Web Data visualization Publishing Service (business) Knowledge management Semantic analytics Semantic Web Data mining Social Semantic Web

Metrics

0
Cited By
0.00
FWCI (Field Weighted Citation Impact)
59
Refs
0.10
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Topics

Data Visualization and Analytics
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Complex Network Analysis Techniques
Physical Sciences →  Physics and Astronomy →  Statistical and Nonlinear Physics
Web visibility and informetrics
Physical Sciences →  Computer Science →  Information Systems

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