Filed under: Visualization
Data visualization is an art of its own, as well as a bit of an obsession of mind, and when it is done well pieces can emerge with forms that are just as interesting to look at as paintings on the wall. Awhile ago I came across a particularly lovely specimen that recently became even more intriguing when I realized that the visualizations were not only beautiful and informative but also interactive.
Eigenfactor: Visualizing Information Flow in Science was created by Moritz Stefaner (also created the super cool Map Your Moves). The project includes four interactive visualizations based on the emerging patterns in scientific citation networks that he developed in cooperation with the Eigenfactor Project. I’ve included explanations of each of visualization as well as screen shots of the interactivity.
The first visualization, and by favorite, titled “Citation Patterns” provides“an overview of the whole citation network. The colors represent the four main groups of journals, which are further subdivided into fields in the outer ring. The segments of the inner ring represent the individual journals, scaled by Eigenfactor™ Score. In the initial view, the top 1000 citation links are plotted. Line size and opacity represents connection strength. The Bezier curves follow the hierarchical cluster structure, using the hierarchical edge bundling technique (pdf). Selecting a single journal (inner ring) or whole field (outer ring) displays all citation flow coming in or out of the selection. The color is based on the cluster color of the origin node.”
The second visualization “Change over time” is something of a combination of a Sankey diagram (example here) and a stacked bar chart that makes a cool display to show the, “changes in Eigenfactor™ Score and clustering over time. The columns corresponds to the years 1997, 1999, 2001, 2003 and 2005. In each year, the journals are grouped vertically according to their cluster structure; within a cluster, they are ordered by their Eigenfactor Score. Bars belonging to the same journal are connected. Clicking highlights both the selected journal over the years, and all clusters it has been part of. This allows to track both changes in journal influence as well as changes in cluster structure. You can see, for instance, the Astrophysical Journal change its cluster from 1997 to 1999.”
The third visualization titled “Clustering”“displays a hierarchical clustering of journals in the form of a treemap. The size of a journal marker corresponds to its Eigenfactor™ Score. Click one of the squares in order to see the amount of citation flow from other journals. The black arrow indicates outgoing citation flow (from the selected journal), the white one incoming citations. The arrow size indicates the amount of citation flow.”
Lastly, there is “Map”, the fourth visualization which, “puts journals, which frequently cite each other, closer together. You can drag the white magnification lens around to enlarge a part of the map for closer inspection. Clicking one of the nodes will highlight all its connections. If a journal is selected, the node sizes represent the relative amount of citation flow (incoming and outgoing) with respect to the selection; otherwise, they are scaled by their Eigenfactor™ Score.”
