Lingjie Wang

This graph shows the cash solvency (capability of covering short-term bills with on-hand cash) of all states. I think it’s a good example of spatial and continuous (ordinal) data visualization.

First, the color scheme is monochromatic, which is fairly reasonable, as it wants to present continuous data: ability assessed by a numerous criterion (Fiscal condition index). Based on that, all states are classified into 6 ordered groups accordingly, which turns the data into an ordinal type, and thus the graph provides 6 clear and distinguishable levels of green color to represent 6 different groups. Also, the ordered values (cash solvency) are represented in a perceptual order: deeper green for higher ability. What’s more, this map provides clear and white colored state borders, which is easy to recognize between green colors, to help viewers distinguish each state.

2)bad example-1:

source:http://www.biopreferred.gov/BPResources/files/EconomicReport_6_12_2015.pdf

This figure shows the global production capacities of bioplastics in 2013. It intends to show both the total production of 9 different types of plastic and also the proportion of biodegradable and biobased/non-biodegradable plastic production in each type. It indeed does a good job presenting the total production, but I think it may need to make some changes for presenting different types of biodegradable and non-biodegradable plastic.

Firstly, the combination of hues and saturation is actually confusing. It chooses three different hues (orange, green and blue) and each has two colors with different grayscale values. We can see from the bottom that there are two groups of plastic: biodegradable and non-biodegradable, and the biodegradable plastic includes both soft orange type, darker orange type, the non-biodegradable plastic includes both soft green type, darker green type, while the soft and darker blue types are classified into two different groups. As we intuitively see darker color as “more” compared to softer color, the figure is confusing as we do not understand whether the grayscale is for the comparison between or inside these two groups.

Moreover, it is difficult to compare the proportion of different types based on the stacked bar charts without exact numerous data, especially for those with very small length, such as the proportion of other (non-biodegradable) type of flexible packaging and rigid packaging plastic.

Bad example-2:

Source: http://pubs.usgs.gov/wri/wri994279/pdf/wri994279.pdf

This graph presents arsenic occurrence in water from 18,850 wells and springs of the United States. It classifies wells and springs into 4 groups ordered by the content of arsenic in water, and shows the distribution of such 4 types of wells and springs in a map.

Roughly, the graph provides an image about the density of wells and springs with different content levels of arsenic in different states. However, there are still some problems in the way of presenting such information. Firstly, in places with lower density, it is easy to distinguish each type and the number of wells and springs. Nevertheless, in places that the locations of such wells and springs are close to each other, it becomes quite difficult to separate red & orange types and grey & green types. Also, as we do not know which type of wells and springs are placed at the bottom, which are placed on top, there may be some triangles covered by others, for example, orange and grey triangles covered by red ones, and that will possibly mislead the viewers to make a wrong judgment about the proportion of each type.

3)Botanical tree:

According to the perceptual and cognition factors, I think there are some problems about these figures. In the article, figure 12 and 13 show the “Unix directory of one of the authors”. (And I don’t think I fully understand the content of these figures, as there’s no explanation near.)

Firstly, the combination of 3-D display and size variation makes it difficult to compare the actual size of phi-balls and cones. If it is presented in 2-D, the size comparison is clear and easy. However, as in 3-D display, more distant objects become smaller, it is hard to make a conclusion that whether this phi-ball looks smaller because it’s more distant from the screen than the other, or simply because it’s actually smaller in size.

There are also some problems about color. We can see that the saturation of color has specific meaning in these figures, and when it is mixed with shadows, which is a feature of 3-D display, it will be hard again to clearly recognize the exact color of each branch, ball and cone. Also, there may be too many different colors in a same graph, and the red-green color choice may make people with red-green color blindness distort the conclusion based on the graph.

I have neither given nor received aid while working on this assignment. I have completed the graded portion BEFORE looking at anyone else's work on this assignment. Lingjie Wang