
pmid: 16779135
pmc: PMC1560567
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.
PubMed, Knowledge Bases, Information Storage and Retrieval, Databases, Bibliographic, Medical Subject Headings, Bibliometrics, Data Display, Cluster Analysis, Programming Languages, Periodicals as Topic, Algorithms, Medical Informatics, Software
PubMed, Knowledge Bases, Information Storage and Retrieval, Databases, Bibliographic, Medical Subject Headings, Bibliometrics, Data Display, Cluster Analysis, Programming Languages, Periodicals as Topic, Algorithms, Medical Informatics, Software
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 157 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 1% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
