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Journal article
Making sense of the evolution of a scientific domain: a visual analytic study of the Sloan Digital Sky Survey research
Scientometrics, v 83(3), pp 669-688
01 Jun 2010
Abstract
We introduce a new visual analytic approach to the study of scientific discoveries and knowledge diffusion. Our approach enhances contemporary co-citation network analysis by enabling analysts to identify co-citation clusters of cited references intuitively, synthesize thematic contexts in which these clusters are cited, and trace how research focus evolves over time. The new approach integrates and streamlines a few previously isolated techniques such as spectral clustering and feature selection algorithms. The integrative procedure is expected to empower and strengthen analytical and sense making capabilities of scientists, learners, and researchers to understand the dynamics of the evolution of scientific domains in a wide range of scientific fields, science studies, and science policy evaluation and planning. We demonstrate the potential of our approach through a visual analysis of the evolution of astronomical research associated with the Sloan Digital Sky Survey (SDSS) using bibliographic data between 1994 and 2008. In addition, we also demonstrate that the approach can be consistently applied to a set of heterogeneous data sources such as e-prints on arXiv, publications on ADS, and NSF awards related to the same topic of SDSS.
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Details
- Title
- Making sense of the evolution of a scientific domain: a visual analytic study of the Sloan Digital Sky Survey research
- Creators
- Chaomei Chen - Drexel UniversityJian Zhang - Drexel UniversityMichael S. Vogeley - Drexel University
- Publication Details
- Scientometrics, v 83(3), pp 669-688
- Publisher
- Springer Nature
- Number of pages
- 20
- Grant note
- 0612129 / National Science Foundation (NSF)
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Information Science; Physics
- Web of Science ID
- WOS:000277418400006
- Scopus ID
- 2-s2.0-77952322113
- Other Identifier
- 991019168766704721
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Web of Science research areas
- Computer Science, Interdisciplinary Applications
- Information Science & Library Science