Critique of America’s Poorest Poor by The Guardian Data Blog

The first thing I noticed about the visualization of poverty and wealth growth in the U.S. was how attractive it was overall. I liked the simplicity in the design of shapes and colors because they reminded me of a sort military map meets modern art piece. Another positive element of design with the graphic below the map, which compensated for the problem of two-colors not really being able to show how bad the areas with poverty really were.

The user-interface of the interactive was not as awesome when it came down to playing around with it. I would have added a function to drag the map, which this map did not include and it made zooming in and out kind of complicated. Luckily, the designer was smart enough to include a “home” button which returned the map to its original state. I didn’t see the point of being able to click on a state and make it light up at first because so many of the states on the bar/candlestick chart below don’t have colors that light up because compared to New York or Detroit, their stats are not as dramatic. To fix this I think I would have made sure that the bars were adjusted to that every city had the correct proportions, but each city also had color and could light up. This function is also important because the cities in the bar chart are organized by rates of poverty and unless you only want to see the top cities with the greatest change, it can be difficult to look for the city you want.

Overall, I really enjoyed this visualization and liked the scaffolding provided, there are just a few things that I think the designer could and should have added to make the graphic as user-friendly as possible.


Data Critique: Bicycle Accidents

This week, I looked at bicycle accident data analyzed in this visualization from the Bay Citizen. I think last week, Keldy chose a similar visualization, but I think this one used the data in a way that I personally found more useful. I liked that the menu on the side allowed the user to track exactly what he wanted to look at, I liked the different types of tabs that could be removed or added to the menu.

One thing I didn’t like about the visualization was that it wasn’t terribly clear what each tab meant. I don’t think it was ever clearly defined what a hotspot meant, and I found it confusing that there weren’t specifications as to what those accidents were on the info bubbles and that you had to click through to get more information. It was especially inconvenient because there was so much room on the info bubble, that at least for some of the hotspot cards, the designer could have added more information.

That being said, I really liked the design that they put into the info bubbles in general. Overall, those particular parts are often ignored, but I found these to be compelling, especially if the map itself was mostly going to be filled with different kinds of points.

Food Atlas from USDA–Bringing Data to the People (With A Malfunctioning Map)

This week, I had to work with a Food Atlas map made by the USDA to explore stories within food distribution and programs throughout the United States. The map was compiled using numbers on everything from the number of students who accepted free lunches in each county, the ratio of prices between soda and milk per county, the obesity levels per county, the number of people without a vehicle who lived more than ten miles from a grocery store…etc. The list goes on and on. Although the USDA did a great job of compiling data, which can be viewed in a massive downloadable .CSV file, the map itself I find borderline useless.

The first of my problems began when I wanted to zoom into the map and then move around. Most maps (like Google maps, for instance), allow the user to grab the map and pull the location across the screen. With this map, this only clicked on whatever county you were currently near and made an annoying little bubble pop up (this must be where scaffolding goes awry). And once that tiny box pops up, do you think you can use your mouse or scroll pad to scroll through all those statistics? Yeah, right! That will only zoom you in or out of the map itself which could take another two minutes to load up again. If you have already zoomed in and want to move the map at all, you must use the tiny arrows at the top of the map screen.

If you want to compare data, you must click on the counties and have them “selected,” but these use a different color scale than the rest of the map, including the map key which is located on the side. This makes the map incredibly difficult to use and perhaps discourages users from looking at all of the statistics that the USDA has. All in all, I think it was a good use of data, but could have been achieved in 1,000,000 better ways than this.

In fixing it, I think the main problem is the sheer amount of data that they are making you look at. What could be easier would be if they had several tabs, where users could look at information by state or by county. Meanwhile, users could also click tabs (like they can on an individual county basis) to see changes throughout the whole map without having to click a million different counties. USDA could have also just made a few different maps comparing correlated things like obesity and amount of fast food restaurants or farm to schools programs and the number of students who receive free lunches.

In terms of color, I would also have the color be a little darker, or use a pop-out function for the counties, so that the “selected” counties were not on an entirely different color scale than the rest of the map. The sad thing is, most of these functions can be carried out in a much easier and more efficient program–Google Fusion Tables.

Critique of Wired’s Wireframe

Because of our reading and our own wireframe illustrations, I decided to do this week’s critique on a wireframe from Wired Magazine’s homepage. The frame itself seems to be on a 6- or 12-column grid, on which it lays out things with variable symmetry, font and style.

The first thing is the page’s title, which is a graphic with varied lettering, almost preparing the user for the varied fonts and a chaotic page layout. However, while the page seems like a lot to look at, it’s actually very symmetrical and properly lined up. There are five stories and three photos at the top of the page, but they are neatly put into two columns–one with two stories, the other with three. Below that, there is a navigation bar with the different sections of the magazine that the user can click on.

I actually dislike Wired’s navigation bar because I find that their drop-down menus have too many options and also that some of their sections within the navigation don’t have drop-downs at all, making it slightly confusing for the user as to what they will find when they click on the section.

Underneath that, they have a section that is divided into three columns. The column on the right contains ads, photo slideshows or videos, the column on the left has articles with photos and the headlines in a smaller size of font, and the column in the middle just has article heads and decks in a large version of the same font. Above each article in what I think is Futura, capitalized, is one word or phrase that the article fits under. “LIFE,” is one, “GEEKDAD,” is another, along with “CEGLIA V. ZUCKERBERG.” I liked this part of their page in particular, because it had the look of chaos without actually overwhelming the reader. The column heads might end in different places, or one deck may be a line longer than another, but they all start at the same row on the page, so the user can easily navigate where all of the stories are.

Then Wired has two tabs with the latest blog posts and hottest links, but these are set up in a pretty lazy way. Particularly with the blog posts, which contains a head and a blurb which is sometimes left with an elipsis, I found that it just looked like a blob of text, especially compared to the rest of the aesthetically-pleasing page.

If I were to redesign Wired’s page, I would start with the navigation bar and try to limit the amount of things on my drop-down menus, then make them into more of a horizontal drop down instead of these weird squares of text that are there now. I would also change the blog posts/web links section at the bottom to make it more appealing. To do this, I would probably have fewer blog posts and weblinks posted, but have color instead of just black headlines–maybe include a couple of photos (with permissions from the blog) and then instead of having which blog it is using text, maybe take the blog’s logo if it has one and put From: [Insert LOGO IMAGE here]. I would also have more space between blog posts so the whole section looked less like a massive block of text.


Data Critique: Wall Street Journal’s IPO: Go, No-Go?

For my critique this week, I took a look at this interactive graphic from WSJ which displayed various dot-com company initial public offerings in the form of a line graph. This chart displayed anywhere from 21 companies all at once to one company at a time, depending on user preference. It allowed the user to examine which companies had made investors a lot of money and which investments were completely bogus. The Y-axis was organized in IPO dollar amounts by billions of dollars and the X-axis used years. This I thought was interesting, particularly because it allowed the user to see a sort of company history. For example, I had no idea that Yelp had only gone public in 2011 or that LinkedIn had gone public very recently because the two companies have been around for at least three years as far as I know. You can also see a broader market history through the data, like when the stocks crashed and prices fell in 2009.

Some things I didn’t like about the graphic were the color schemes–I know it’s probably impossibly difficult to find 21 different colors that won’t be confusing, and WSJ gave it their best shot but Yelp and, at least on my screen are the exact same color. In addition to that, because Yelp became public so recently, it gets lost in the shuffle when you add other companies in and does this weird disappearing thing. I also didn’t like how companies were organized at the bottom. Why do you have to scroll sideways to see all the companies? Couldn’t they have organized them vertically so no scrolling would be involved? This doesn’t even make sense from the designer’s perspective because I would think that just having the page be longer would be better than having a scroll bar. Maybe they wanted to make sure the user could have the color key right next to the graphic in case he or she wanted to compare colors?

Overall, I thought this was a very useful graphic that could be studied by investors and market analysts alike to view market history and potential trends.

Summary of Bubble Trees

The bubble tree paper discusses a problem we have mentioned in class before when doing data visualizations. The issue is illustrating some piece of specific information while not removing it from its broader context. I think that the bubble visualization does this well, however, I wasn’t fond of the example used by the author. I found that the bursting bubble tree in which the mammal could be split up into species and could presumably be split up after that was an interesting idea but I wanted some examples of other data types that this visualization would bode well with.

I think, for example, that this would be a great visualization if you were dealing with something with a hierarchy, like trying to explain the U.S. government and which departments things fall under. It could also maybe work as a family tree when trying to look at historical information.

Critique of The Guardian’s Carbon Emissions Graphic

This visualization is using data from 2007, but I still think that it does an interesting job of representing countries by the size of their impact with a particular issue (in this case, carbon emissions), and not by the size of the country itself. When discussing environmental issues, I think looking at this map by the Guardian is particularly striking because the countries are in their normal locations, but re-sized to match the level of carbon emissions they produce. I also liked how the level of carbon emissions are inside each country’s bubble, however, I don’t understand what the little triangles inside the bubbles are or what they represent.

This graphic has several other elements, including a list of the countries revealing which emit the most carbon. The worst is, of course, the U.S., with China following behind. Even this I found to be done quite thoughtfully because the countries’ colors on the list match its colors in the bubble map. One thing I didn’t like about this list though, was that the numbers in the bubbles were repeated within the list which I found to be a little redundant. I think they could have been left off the bubbles and kept in the list because the list was more legible for every country.

To the right of the list is a graph of global warming and its correlation with carbon emissions, which I don’t think really adds very much to the graphic other than to address why the data is important.  Maybe it’s because it’s 2012 now, but I think that the global warming/carbon emission correlation is kind of obvious by now.

I also think that the checklist below is more depressing than useful and it seemed to make guess claims rather than ones backed by data. The items discussed at Copenhagen seemed to me to be better suited for a sidebar item rather than worked into the visualization itself.

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