The Structure and Dynamics of Scientific Knowledge - Mapping Scientific Frontiers: The Quest for Knowledge Visualization - page 171

Fig. 5.4 A document co-citation network of publications in Data and Knowledge Engineering

Traditional citation analysis is typically biased to journal publications due to the
convenience of available citation data. Expanding the sources to other scientific
inscriptions , such as topics, proceedings, grant proposals, patents, preprints, and
digital resources on the Internet, has begun to attract the attention of researchers
and practitioners. In 2002, when I wrote the first edition of the topic, we anticipated
to see a sharp increase in patent analysis and studies utilizing Web-based citation
indexing techniques in the next 3-5 years because of the growing interest and
commercial investments in supporting patent analysis with knowledge discovery
and visualization techniques. Today, major resources for citation analysis in-
clude Thomson Reuters' Web of Science, Elsevier's Scopus, and Google Scholar.
Figure 5.4 shows a visualization of a document co-citation network of publications
in Data and Knowledge Engineering . The color coded clusters indicate the focus of
the community at various stages of the research. The most cited paper is the one that
invented the entity-relationship modeling method by Peter Chen.

5.3.1.1 Specialties

In information science, the term specialty refers to the perceived grouping of
scientists who are specialized on the same or closely related topics of research.
Theories of how specialties evolve and change started to emerge in the 1970s
(Small and Griffith 1974 ). Researchers began to focus on the structure of scientific
literatures in order to identify and visualize specialties, although they did not use
the term “visualization” at that time.