A team of researchers, Tamara Munzner, K. Claffy, Eric Hoffman and Bill Fenne, as part of Tamara’s hyperbolic mapping research at Stanford University, developed an information visualization tool that could both depict geographical location and charateristics of Multicast Routers arounds the globe. The main objective of the visualization was to understand the structures and efficiency of MBone tunnels. In the visulization an arc would be drawn from one end point of a tunnel to another taking the shortest geodesic arc along the earth’s surface. The height of the arc would be computed from the length of the tunnel and higher arc height would correspnd to longer tunnel length. Arc would also be encoded with colors and thickness to represent certain similar characteristics or type of the tunnels together. The users could interactively move around the view and select only a group/type of tunnels to be displayed to avoid clutter. To enhance visual clarity even more, the tool implemented “Threholding” whereby a subset of the tunnel lines would be drawn in short around the end point center.
This visualization was very useful as it allowed users to view all MBone tunnels in one shot and also understand their spatial distribution without any explanation. The longest tunnels were the most significant tunnels as they would contribute more to congestion and this tool made those tunnels stand out loud with longer arc heights. With a mere glimpse, a system admin could tell which tunnels were the most significant ones. Also, tunnels would be distinctly color coded along with drawing them with different line thikness to classify tunnels based on similar characteristics and type. A group of tunnels could also be selected by the user and the rendering would be limited only to that group to enhance clarity (as shown in figure 2).
One of the most useful features of this visulization is how it implemented 3D navigation; an user could select any point on the surface of the globe as the centre of rotation which allowed proper view of the horizon and differentiate different arc heights clearly. Finally, the visualization data would be distributed using VRML format, which could be used by any VRML renderer or browser. Also they used the VRML hypertext option to embed textual data/description with their visualization data.
NASA: Analyzing Lowell’s Cloud
NASA sattelites have been tracking a new tropical storm called Lowell churning in the Pacific near south east of California. The Aqua Satellites of NASA can measure the cloud temperature and predict the strength of the storm. Figure 1 shows one of the scientific visualization of one such Aqua Satellites.
The visualization only leaves the reader guessing about the color coding as it shows no legend or labels. An intuitive guess would be that red corresponds to higher temperature but it is not really clear what the magenta patch in the middle corresponds to or how the temperatures can really be compared. Also, the visualization doesn’t give any spatial scale whereby the reader can figure out the size of the storm. There is also no indication of the direction of the storm movement. A border map of the west coast of United States is given too but a label of the exact location of few nearby or endangered cities would have given the reader a much better understanding of the potential regions under risk. Overall, this is an example of a bad visualization which fails to give any good information to the reader.