Making Sense of the Evolution of a Scientific Domain: A Visual Analytic Study of the Sloan Digital Sky Survey Research

TL;DR

This paper presents a novel visual analytic method that combines clustering and thematic analysis to study the evolution of scientific research domains, demonstrated through the Sloan Digital Sky Survey's astronomical research from 1994 to 2008.

Contribution

It introduces an integrated visual analytic approach that enhances co-citation analysis by combining spectral clustering and feature selection for better understanding of scientific domain evolution.

Findings

Successfully analyzed SDSS research evolution from 1994 to 2008.

Applicable to heterogeneous data sources like arXiv, ADS, and NSF awards.

Empowers researchers to visualize and interpret scientific knowledge diffusion.

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.