Visualizing Knowledge Domains
by Katy Börner, Chaomei Chen, & Kevin Boyack (in press)
Annual Review of Information Science & Technology, Volume 37.

Figure 1. Process flow for mapping knowledge domains.
Figure 2. Numbers of articles in the ARIST data set by year with terms (ISI keywords) or abstracts.
Figure 3. Numbers of articles by field per year in the ARIST data set with average citation counts. Articles contribute to counts in more than one field if retrieved by queries from multiple fields.
Figure 4. An overview of the author co-citation map (1977-2001), consisting of 380 authors with 9 or more citations. The map is dominated by the largest specialty of citation indexing. No strong concentration of other specialties are found, which implies the diversity of the domain.
Figure 5. A landscape view of the ACA map displayed in Figure 4. The height of a citation bar indicates the number of citations for the correspondent author. The spectrum of colors on each citation shows the time when citations were made. Authors with more than 50 citations are displayed with semi-transparent labels.
Figure 6. An overview of the document co-citation map of 394 articles with 10 or more citations. In this network, a number of tight clusters of documents are connected to an artery-like chain. Documents on the artery chain tend to be seminal works of connected clusters. For example, Diana Crane's Invisible College (Crane, 1972) connects the scholar communication cluster to the artery chain.
Figure 7. A landscape view of the DCA map displayed in Figure 6 at distance.
Figure 8. A close-up view of a few clusters along the main artery in the DCA map. The height of a bar represents the number of citations to a publication. Labels indicate articles in clusters, for example, Small73 for an article of Small in 1973. Multiple publications within the same year are not distinguished at this level. For example, Small73 includes all Small's publications in 1973.
Figure 9. ET-Map of the ARIST data set using keywords. Left is a list of labels of all categories. A user can select a category of interest and the interface will display documents within that category.
Figure 10. Cartographic SOM map of ARIST data set.
Figure 11. VxInsight citation maps of ARIST data for four different time segments. Circles indicate areas highlighted in the text. Dot color legend - WHITE: citation analysis, GREEN: bibliometrics, BLUE: semantics, MAGENTA: visualization.
Figure 12. VxInsight co-term (left) and LSA (right) maps of ARIST data.
Figure 13. VxInsight co-classification map of ARIST data
Figure 14. Comparison of layouts of four different document maps based on terms or words. A: Cartographic-SOM (compare Figure 10), B: ET-Map (compare Figure 9), C: Co-term (compare Figure 12, left), D: LSA (compare Figure 12, right). Dot color legend - YELLOW: citation analysis, GREEN: bibliometrics, BLUE: semantics, MAGENTA: visualization.
Figure 15. Strong co-term linkages based on cosine similarity for the three term-based document maps of Figure 14.
Figure 16. Comparison of distinct fields on the citation map with their counterparts on the term or title-based maps. Legend - BLUE: author co-citation (ACA), GREEN - co-word analysis and Leximappe, MAGENTA: co-citation analysis.

Last Modified: July 26, 2002