CiteSpace II: visualization and knowledge discovery in bibliographic databases.
This article presents a description and case study of CiteSpace II, a Java application which supports visual exploration with knowledge discovery in bibliographic databases. Highly cited and pivotal documents, areas of specialization within a knowledge domain, and emergence of research topics are visually mapped through a progressive knowledge domain visualization approach to detecting and visualizing trends and patterns in scientific literature. The test case in this study is progressive knowledge domain visualization of the field of medical informatics. Datasets based on publications from twelve journals in the medical informatics field covering the time period from 1964-2004 were extracted from PubMed and Web of Science (WOS) and developed as testbeds for evaluation of the CiteSpace system. Two resulting document-term co-citation and MeSH term co-occurrence visualizations are qualitatively evaluated for identification of pivotal documents, areas of specialization, and research trends. Practical applications in bio-medical research settings are discussed.
Synnestvedt
Marie B
MB
Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania School of Medicine, Philadelphia PA, USA.
Chen
Chaomei
C
Holmes
John H
JH
D000465:Algorithms; D015706:Bibliometrics; D016000:Cluster Analysis; D003626:Data Display; D016206:Databases, Bibliographic / Q000706:statistics & numerical data / Q000639:trends; D016247:Information Storage and Retrieval; D051188:Knowledge Bases; D008490:Medical Informatics / Q000706:statistics & numerical data; D046650:Medical Subject Headings; D010506:Periodicals as Topic / Q000706:statistics & numerical data; D011381:Programming Languages; D039781:PubMed / Q000706:statistics & numerical data / Q000639:trends; D012984:Software