The circle display is a super neat idea. The only thing that seems a little troubling is that adjacent sets of spokes visually look like they’re more related than those farther away — and as far as I can tell, that’s not true.

I really wish the triangle-star view worked better. The idea of tricking our eyes into completing lines is quite neat. However, I’m not entirely sure those patterns would mean a lot in the data — I think this transformation leaves some axes in places where you’d expect spatial correlations, and some axes in places where you wouldn’t, and it’s not apparent which is which.

The circles are a really neat idea. This visualization is clean, simple, and shows a lot of information. I prefer the length encoding over the thickness encoding. It’s easier to distinguish between lengths since the circles are so small.

I like the animation too, but I think it might be more effective if the bars actually shrunk and grew, instead of just crossfading from one configuration to the next.

The second visualization is more like an oblique bar chart. Since for oblique designs, there might be two sets of useful resources for coding: the oblique angle and the width of one edge of the trangle, some further modification might be worthy.

I like the third design very much. Though it basically concealed the relation ship between the whole matrices and between nodes and nodes, it compares each node value of different matrices very clearly.

The problem of the final design might be scalibility. Cluttering problems might be extremely serious with more matrices to compare with.

The presentation seemed to imply that the density visualization failed, but I thought there was a lot of promise in it. It seemed like the idea almost correct and the visualization captured it perfectly.

The second visualization is a very aesthetically pleasing view; however, I’m not really sure what the color encoding on the view represents. Since there is a discrepancy in color, it’d be nice if this was a data encoding.

The third visualization is very difficult to make comparisons between nodes, but the length encoding does go a long way to explain relationships within a node across networks.

The animated visualization provides a nice visualization in terms of manipulating the temporal dimension. It would be nice, however, if the user could have interactive control of the changes in time, it would be a lot easier to use the visualization in a more analytical sense.

The final visualization definitely utilizes pop-outs well; however without more detail with regard to what the visualization is actually showing, it’s really difficult to understand what it is showing.

I like the circles for several reasons, but mostly because it creates a quick snapshot. I would probably reduce the size and thickness of the inner circles so that more ‘ink’ is given to the lines representing data.

The animation is helpful for making comparisons but it would probably be more useful as an interactive demo, so that comparisons could be made in a non-linear manner.

Nodecircle visualizes all the required elements and is quite neat. If the spikes distribute equally along the circle, it will make it easy to view when there are more spikes.

The comparison between triangles tends to emphasize the upper parts. Maybe it is still better to keep using upper/lower triangles, which can help locating the original data.

The bar chart visualization is nice, but it is not easy to make comparisons between more than three matrices at once. Perhaps showing the others in a grayed out manner and switching contexts would help with this?

I like how the ring based visualization shows the centrality value with color, and the more fined grained data with length/thickness

In the second design, it’s somewhat difficult to compare thickness of lines and darkness of the grey, especially when there is no overlap. It’s hard for me to look between all three an make any meaningful judgements.

The circles are nice and I think relatively comparable between them. It is taking and egocentric view, but looking across multiple data sets. I think labels are necessary, as I cannot tell if the specific skills are ordered in clockwise/counterclockwise fashion, or if they are mirrored symmetrically.

The progressing bar animation is an interesting way of showing change between data sets. It would be nice to just pause and switch through the different views instead of animating it, just so that we can focus on the data being seen.

The last visualization needs some explanation. I can somewhat compare between the two datasets, but it might be better to see two triangles side by side rather than overlapping.

The second design is simple, but some text will make it more understandable and in
this design, there is freedom to choose many colors. One problem that I see with this design is that when the dimension grow, the inclined line will come closer and it will be hard to differentiate.

The third design is simple, and it will provide more information if text is also used to convey the what each spike represent. May be different dimension can have different color. Overall it is a good design.

The fourth is simple and standard technique. The contrast in colors are nice. Display of legends convey useful information.