Logo image
Visualizing a Field of Research: A Methodology of Systematic Scientometric Reviews
Journal article   Open access

Visualizing a Field of Research: A Methodology of Systematic Scientometric Reviews

Chaomei Chen and Min Song
PloS one, v 14(10), pp e0223994-e0223994
11 Jun 2019
PMID: 31671124
url
https://doi.org/10.1371/journal.pone.0223994View
Published, Version of Record (VoR) Open

Abstract

Computer Science - Digital Libraries ESI Highly Cited Paper (Incites)
PLoS ONE 14(10): e0223994 (2019) Systematic scientometric reviews, empowered by scientometric and visual analytic techniques, offer opportunities to improve the timeliness, accessibility, and reproducibility of conventional systematic reviews. While increasingly accessible science mapping tools enable end users to visualize the structure and dynamics of a research field, a common bottleneck in the current practice is the construction of a collection of scholarly publications as the input of the subsequent scientometric analysis and visualization. End users often have to face a dilemma in the preparation process: the more they know about a knowledge domain, the easier it is for them to find the relevant data to meet their needs adequately; the little they know, the harder the problem is. What can we do to avoid missing something valuable but beyond our initial description? In this article, we introduce a flexible and generic methodology, cascading citation expansion, to increase the quality of constructing a bibliographic dataset for systematic reviews. Furthermore, the methodology simplifies the conceptualization of globalism and localism in science mapping and unifies them on a consistent and continuous spectrum. We demonstrate an application of the methodology to the research of literature-based discovery and compare five datasets constructed based on three use scenarios, namely a conventional keyword-based search (one dataset), an expansion process starting with a groundbreaking article of the knowledge domain (two datasets), and an expansion process starting with a recently published review article by a prominent expert in the domain (two datasets). The unique coverage of each of the datasets is inspected through network visualization overlays with reference to other datasets in a broad and integrated context.

Metrics

11 Record Views
1067 citations in Scopus

Details

InCites Highlights

Data related to this publication, from InCites Benchmarking & Analytics tool:

Highly Cited Paper 
Collaboration types
Domestic collaboration
International collaboration
Web of Science research areas
Information Science & Library Science
Logo image