Barton and Barton and Maps

In this reading Barton and Barton discuss a couple of different things having to do with maps. The two big main things that they discuss that I am going to cover are the rules of inclusion and the rules of exclusion. In terms of map making the rules of inclusion determine whether something should be mapped, what aspects of a specific thing should be mapped, and how should the mapped aspects be represented? One example from the reading is the Hachette World Guide in which the man who wrote it seemed to be overly describing how beautiful the mountains were and he basically considered any area that had uneven ground to be a picturesque mountainous place. For the rules of exclusion Barton and Barton talked about how studying what someone making a map chose not to put on the map can be just as telling and informative. In this section they talk about how in European cartography the people making the maps during a specific period in time seemed to not even bother including things or making maps for the lower classes that they deemed as not being able to understand or use maps.

I found this reading to be pretty dry and boring, but how Barton and Barton looked at and examined maps gave me a few useful details into how I could approach designing something. There examples about not trying to hard and overselling something because it serves a specific interest was very insightful and reading about the European map makers did give me a good look at how I should maybe not design something to specific and always be mindful that what I am making will inevitably be seen by people who maybe have no idea what the designed object is for but that doesn’t mean they should not be able to get any information from it at all. Below is a map of Middle Earth that when it was drawn used some of the inclusion and exclusion rules from the reading. There is definitely mountains and forests shown on the map but not every tree is shown and not every city or town, just the ones deemed most important by the cartographer for us to know or remember.


My question is this: can you think of ways that these principles and rules can carry over to graphic design or at least motion graphics design?


Dombrowski: A look at a Celebrex Ad

For today’s reading we had a very short 5 page reading about the unethical way in which a drug company was advertising one of its’ drugs. The company Pfizer Pharmaceuticals created an ad for one of its’ drugs called Celebrex back in 2005. This ad caused some controversy and ended up getting studied by Dombrowski to determine how it had unethically showed information, especially information having to do with critical results of certain tests on the drug and possible side-effects. Dombrowski talked about a few things that the Celebrex ad did that were unethical. The first thing that they did involved the overall tone of the ad. In the ad there were people going about their day and doing things pain-free and the color being used in the ad was a calming blue color which is used to set the audience’s mind at ease. The were setting the ad up to put the viewer at ease even though there were some pretty serious side-effects that could occur. The next issue that Dombrowski had with the ad was that the disclaimer text that all drug ads are required to have, the text that explains certain side-effects and other issues or problems that most drug ads have very small at the bottom of the screen, the Celebrex ad decided to make the outlines of the people and animals in the ad made out of the text. This was an issue because it made the text so small and inconsequential that it was basically not a part of the ad anymore. The only time the text was readable was when the ad pulled specific words or phrases out to reinforce the narration and make the drug seem more safe than it really was. The last issue Dombrowski noted was that information about some of the problematic trials that Celebrex had had and information about a possible linked to increased risk of heart attack were not present in the ad at all, which is totally unethical.

I totally agree with Dombrowski in this article. I believe that what the Pfizer Pharmaceutical company did with its’ Celebrex ad was completely manipulative and unethical and I am glad that the FDA had issues with it back in 2005. We have been learning that the audience should come first in the world of motion graphics, because knowing your audience and catering to them is the best way to make your advertising or message effective. It is pretty apparent that this company didn’t have much respect for their customers and just wanted to make money from this drug.

Below is another example of unethical advertising. This is an ad for cigarettes in which the ad portrays a “dentist” recommending the cigarettes over other cigarettes. This is unethical because this isn’t a real dentist and there is no data that shows that this cigarette is better for your teeth than any other cigarette, and even if there was it means nothing coming from a fake dentist.


My question is this: do you think that even when the text at the bottom of a drug ad that that makes it ethical to not even mention the information in the narration?

Amare and Manning: Fix Your PowerPoints

In the reading for today Amare and Manning discuss a few different topics, all revolving around creating ethical visual graphics for rhetorical situations. In the beginning of the reading Amare and Manning discuss a few different ways that visual graphics have been broken down and viewed in. They talk about the 6 groups of Elliot and Lester, which are 1) Categorical Imperative 2) Utilitarian 3) Hedonism 4) The Golden Mean 5) The Golden Rule and finally 6) Veil of Ignorance. Then they move on to discuss C.S. Peirce’s topic of ethical actions and then they look at visual rhetoric within the framework of epistemological ethics, which is basically saying that the overall goal of everything that everyone does should be attaining the truth of any given situation. The greatest part of the reading, however, is dedicated to explaining why certain aspects of visual rhetoric are bad and what can be done to improve upon them, this is also the section in which they look primarily at things being displayed in PowerPoint.

I enjoyed the PowerPoint section of this reading the most because it had some pretty good tips that apply not only to designing effective and ethical PowerPoints but to good graphic design in general. One of the biggest things mentioned in this article is that knowing your intended audience is, as we’ve seen in almost every reading so far, the thing that can have the greatest impact on whether or not your graphics are successful. This also plays into C.S. Peirce’s ethical actions because knowing your audience is the best way to make sure that the graphics you are creating are not unethical and that they do not offend the people that you are trying to appeal to with your graphics. Other good topics that are talked about and expanded upon are having clear and limited contrasts in your information and graphics. Too many contrasts becomes ineffective and hard to decipher. You need to filter out irrelevant details and information. If it doesn’t need to be on the screen, don’t put it on the screen, it will only detract from your overall message or goal. Finally, you need to make your point or goal immediately obvious. If you fail at meeting any of these standards than, according to C.S. Peirce, you are creating unethical graphics.

Below is an example of an infographic that show the different costs of the same Starbucks latte in different countries around the world. I think this example does a good job at fulfill the three criteria above, it contains no irrelevant data, has the information it is presenting filtered well and it’s point is very easily deciphered.


My question is this: Do you agree with the Peircean theory that failing any of the three criteria will result in unethical graphics?

Response to Dragga and Voss

In the reading for today we have Dragga and Voss complaining about how they think there is no humanity in the way that data graphics are created today. The majority of this article is dedicated to showing different examples of data graphics that they deem inhumane and then they explain why they believe the graphics are inhumane. A few of these examples are things like two almost identical pie charts sitting side by side, one of them is breaking down the employment by region of lumberjacks and the other one is comparing the different ways that lumberjacks die while on the job. At the end of the article Dragga and Voss provide some hilarious ways they think could humanize data graphics.

While I do agree that many types and examples of data graphics could be considered lacking humanity, I don’t think of this as a problem. I view data and data graphics as being something separated from ethics. It is data, end of story. The data may point to problematic or troubling revelations and the data itself may be troubling, like say a very large number of suicides among teens being reported or something along those lines, but I do not believe that the data or the charts and graphs that we put the data in should be cast in a certain light (good or bad). Obviously, no one is going to look at high levels of suicide among teens and think anything good, I don’t think we need to put pictures of teens behind the data and graphs to “humanize” the data. That seems absolutely ridiculous to me. I believe that the humanizing aspect of the larger point trying to be made shouldn’t have to fall solely on the data itself, because in the end the data is merely a reporting of facts. Even the example Dragga and Voss used of the two pie charts of lumberjacks is ineffective to their argument, to me at least. While it is sad that so many lumberjacks die in many different ways, what does making us sad by looking at the graph accomplish? Data needs to be defined by the argument or situation it is being used in. Humanizing statistics provides no purpose when it is being done purely for the sake of humanizing the statistics.

The example below is a very simple graph of the top 10 most common areas people contract cancer in. I believe this graph would be something that Dragga and Voss would deem “inhumane” because it is dealing with such a heavy and life changing topic but is doing nothing the make you connect with the people who have cancer. I think it would do nothing the have a picture of someone with cancer behind the graph or little icons of sick people on this graph. We all already know that cancer sucks.


My question is this: do you believe that the burden of humanizing the subject in question should fall to the data and the data graphics?

Death from Cholera and Chartjunk

This week’s reading from Tufte was an interesting one. Tufte examines two different historical events which were either helped or hurt by good or bad data visualization techniques. The first example he talks about was a cholera outbreak in London back in the late 1800s. The outbreak was traced back to a contaminated water pump on a specific street by a man named John Snow. He did a bit of detective work and linked the people who died to where they lived, worked, or spent the vast majority of their time during the day. He plotted all of this information on a dot graph on a map of the general area of the outbreak and was able to draw a direct correlation to a specific street, Broad Street, and deduced from there that the water pump was contaminated. He is credited for stopping the outbreak, which Tufte isn’t entirely certain about because it seems that the outbreak was dying down by the time Snow had charted his data and made his findings know, but the amount of cases after Snow’s work was done were significantly lower so there was probably some relation. The other event Tufte analyzes is the explosion of the Challenger space shuttle. The company which made the rocket apparently had strong beliefs that the temperature in which the Challenger would be launching would cause a malfunction of a specific rocket part and low and behold that is exactly what happened. The rocket manufacturer conversed with NASA the night before the explosion to voice their concerns and the sent NASA 13 different charts to try and convince NASA. Tufte says that these charts were lacking elements to make them convincing and they actually provided excuses for NASA to disregard the warnings the rocket manufacturer was giving them. Tufte mentions that the charts lacked specific names of the people doing the research, some of the charts didn’t relate the data directly to the temperature, and others were poorly worded or shown. Even the research into the explosion after the fact produced sub-par, by Tufte’s standards, charts and graphs loaded with chartjunk and unnecessary facts and figures.

Overall, this reading is a good reinforcement of the principals Tufte was championing in the reading of his we had earlier in the semester. You need to put a lot of effort into your charts and graphs to make sure that they have only the most necessary information and that you did the required research to adequately tie your research to the points you are trying to make with your infographics or else the infographics serve no purpose.

The example below is of chartjunk, which Tufte has talked about at length, and is an example of what you should not do if you actually want to get the audience to read and engage with your stats and information.

My question is this: do you believe that poor infographic practices actually have as strong of an impact as Tufte is trying to convince us of in his reading?

Writing For Different Audiences – A Summary of Fahnestock

The article we were to read for today was fairly interesting. It was an article in which Fahnestock looks at and talks about the differences that occur when writing for different groups of people. The article has a few different focus points, mainly the genre shift and the changes in information. Fahnestock mentions something that she calls the “genre shift” which happens when taking information being written for one group and re-writing it for another group. In the reading she looks in depth at instances of this happening within the scientific community. Papers written by scientists about their own studies and experiments are being taken and then reported on by scientific magazines and journals whose core audiences are not other scientists. This leads to a shift in the way that the magazine and journal authors write the information. The scientists, when they write the papers, know that their findings have to withstand judging and testing from other scientists who will read and criticize their work. In knowing this, scientists tend to downplay certain findings and facts and they almost never make wild claims about their findings. This isn’t the case with the authors of the magazines and journals because they are trying to make their articles more interesting. This tends to happen, according to Fahnestock, in two different ways. The “wonder” and “application” appeals. Whenever the magazine and journal authors would write about these important scientific studies and findings they would almost always either use the “wonder” appeal in which the author talks about how new and game-changing these new findings are or they would use the “application” appeal and try to extrapolate on what could potentially come out of these new findings. Fahnestock also talks about the change in information, a trend in which these magazine and journal authors are now focusing more closely on the results of these different studies and not the actual data itself, which can misconstrue the actual findings somewhat.

Even though this article is fairly old, I still see evidence of these two things happening today. On many of the websites and news articles I read, the authors of these pieces tend to make whatever they are talking about seem like it is an amazing discovery with tons of awesome new applications that are going to change everything. The information is rarely as amazing as the article tries to make it seem. The same thing tends to happen with almost everything in the news as well. The focus is shifted away from the facts and onto what this means for the future and trying to figure out the effect of whatever the news topic is. Below is an example from a site I frequent. In the example below the author of the article is reporting on very dark colored matter that has been created by a team of scientists. The author pairs down the actual study to give the audience a more condensed and sensationalized view of the results of the experiment and talks a bit about the “applications” it could have.


My question is this: Fahnestock mentions near the end of her article that the trends she is noticing and writing about can be applied to any field, is what she writes about in this article a issue in motion graphics?

Tufte: Data-Ink Ratios and Ducks

In the reading for today Tufte focuses on a couple of issues that he sees within the world of data graphics. The first half of the reading Tufte talks about a couple of interesting, but fairly obvious, things that someone who is creating data graphics should be aware of. The biggest thing that he stresses in the first half of the reading is that the data is the most important part of the graphics. Tufte says that you should prioritize the data above everything else, which makes sense because the data should be the main focus of data graphics. In prioritizing the data he also talks about the data-ink ratio which is how much of the ink used to create the graphic is actually being used to draw the data. Tufte stresses that you should keep your data-ink ratio high and try your best to erase non-data-ink, which is of course ink that does not create data.

In the second half of the reading Tufte talks about three different types of what he calls chartjunk. Chartjunk is exactly what it sounds like. It is junk that clutters up the chart or data graphic and serves essentially no purpose. The three variations of chartjunk that he talks about are: unintentional optical art, which appear when people use too many distracting elements and they tend to cause the moire-effect which is when your eye perceives motion when there isn’t any, the grid, and the duck. The grid is bad, according to Tufte, because it tends to cause too much clutter and it almost always makes the graph harder to read. The duck is when a graphic uses far too many decorative elements to the point where the data becomes lost in the graphic. All three of these things should be avoided at all costs when designing data graphics.


Above I have two examples of graphs that would be seen as terrible by Tufte, and really anyone. During the reading Tufte talked about something that really resonated with me and that was that too often data graphics are being created by computers in ways that do nothing to help the data or the point of the graphic but to merely show that “computers can do really cool things.” Tufte explains that you should never do this because it jeopardizes the data. Both graphs above are extremely hard to read and comprehend. The one on the left is hard to read because it has a very strange circular design with bars and lines running everywhere within. It creates a very heavy moire-effect on anyone who tries to read it. The one on the right adds a false perspective to the graph and that causes its data to become almost unreadable, the data in the back is almost completely hidden and the data that is seen doesn’t line up very well at all with the grid lines.

My question is this: do you agree with Tufte that successful data graphics should have nothing in them but the bare bones data?