Social Progress Index – Global Data Representation Analysis

Hi Everyone,

For my first CMS.631 assignment, I have chosen a data graphic that is in line with this semester’s theme of Civic Data, which is defined as “Data about our world and how we experience it, being used with the goal of making it better for us all”. This data representation comes from the researchers at the Social Progress Imperative, whose aim is to provide substantive metrics to measure the overall “social progress” of each country in today’s world.

Link for Data Representation

Social Progress Index Data Representation
The data being shown in this information graphic is the aggregate “Social Progress Index Score”, which is made up of three core metrics: “Basic Human Needs”, “Foundations of Well Being”, and “Opportunity”, each with their own four sub-metrics which then have their own data components. This is a massive data endeavor, and many different types of standard metrics such as “Child Mortality Rate”, “School Enrollment”, and “Obesity Rates” are combined with less standard metrics such as “Freedom over life choices” and “Corruption” in order to come up with the aggregated scores. As such, the face-value data that is present is essentially a conglomeration of thousands of economic and social indicators, boiled down to a few key scores and partitioned at the country level.

I think there are multiple audiences for this type of data representation. In my opinion the main one is researchers and policy-makers, in the sense that the data tries to provide a brand new methodology and a massive amount of already finished work for measuring progress as a country (and can be used at different levels of granularity) in a different, more holistic way then today’s methods. I think another main audience is that of those organizations responsible for data collection, in that it provides a clear vision of what kind of analysis and (hopefully) impact can result from certain data sets that are collected. Finally, I think another important audience for this data representation is the general population; this is because all of this complicated data curation, analysis, and representation is boiled down to a few numbers per country with a focus on visual presentation of the information, the information is presented freely online, and the Social Progress Index has been the focus of several TED talks over the last few years.

I think the there are three main goals of this data presentation. The first is to get a conversation going among the general populace with regards to what social progress means, how it is measured, and why different countries have different levels of social progress. The second is to provide decision-makers who may not be that technical with a methodology upon which to have discussions with other decision-makers and also to drive forward policy and research initiatives. The third is to draw researchers into the methodology and analysis done such that they consider the Social Progress Index as an effective metric and measurement system for how the world is changing over time.

I think that the graphic is quite effective, because it allows for different levels of granularity (which serves multiple audiences),  has a strong visual focus (colors help differentiate between metrics and shades of color help to compare different countries), and minimizes the amount of numbers presented (instead uses relative positioning via a ranking and colors to help people orient themselves within the framework presented).

Overall, I found this graphic to be very thought-provoking and incredibly relevant to the world today and the our class’ theme, and had a lot of fun looking through it. I look forward to having many more of these experiences over the rest of this semester!



Ragged Mountain Snowfall

As a member of the MIT Ski Team, I frequently look at the upcoming forecasts, hoping for more snow. Unfortunately, the unseasonably warm weather lately has made training very difficult. This is a chart of yearly snowfall at the team’s home mountain, Ragged Mountain, from It shows for each season from 2010-11 until now, what percentage of average snowfall the mountain has had. Ragged SnowfallThe chart uses circles of different heights to correspond to that’s years percentage, and it also includes different colors of the circles to go along with that. Seasons of low snowfall have orange circles, while seasons with more snowfall have bluer circles.

The audience of this chart is people like me, who ski at Ragged often. Since I’ve been skiing at Ragged for a few years now, I know how much snow they had last year and the year before. So when I look at the chart and see that this year has a much lower mark than the previous couple of years, I have a good sense of how much snow to expect. I believe that that’s the goal of the presentation. It shows skiers the trend in snowfall, in a way that’s easy to compare from year to year.

I think that this presentation is effective because I can easily see that this season I should expect less snow than in recent years, which lines up with what the weather has been like lately. However, one detail I wish this chart included is the actual number of inches, rather than only a percentage. Even just an indication of how many inches “Average” is would be a helpful specification.

CDC’s Women and Risks of Drinking Poster

The Centers for Disease Control and Prevention released an Infographic on the risks of drinking for women last Tuesday as part of their Vital Signs Report. The data displays the risks of drinking alcohol when pregnant. The data also claims that drinking 8 drinks a week, or binge drinking can lead to injuries/violence, STDs, and unintended pregnancies for women, among many other risks, without discussing any other contributing influences.

The audience is doctors, nurses, and other health professionals as the lower half of the poster shows a 5-step guide for helping women avoid drinking too much.

The goals are to show women (or their health professional who will pass on the information) that drinking holds many risks during pregnancy and the general risks of drinking, although the risks are not attributed to anything except for drinking which is absurd.

A small portion of the data displayed effectively shows the risks of drinking while pregnant, which seems to be the main message of the poster. A quote supporting this is on the lower half of the poster that suggests that women trying to get pregnant should avoid drinking alcohol. The biggest problem is half of the data shown on the top half of the poster does not suggest women who are trying to get pregnant should drink less, which is legitimate considering the risks shown when a women becomes pregnant. The poster instead suggests that women use birth control when drinking, insinuating that because women can have children; they are to be held accountable for the risks of drinking, which is why this poster has become so controversial.


Top Half of CDC Poster on Women and Risks of Drinking

Poster Link

Original CDC Article Link

Skittles for days

This “Nursing Your Sweet Tooth” graphic makes a visual argument that we (Americans) are eating too much sugar by hyperbolically representing the amount of sugar the average American consumes over time with absurd physical objects (i.e. in a lifetime, this much).

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The presentation also gives information about the main sources of sugar in the American diet (focusing specifically on soda), and negative health outcomes associated with high intake. The graphic is on, so it seems likely that the intended audience is white, middle to upper class businessmen, who, interestingly, consume comparatively less sugar than lower-income black or Hispanic consumers.

The goal of the data presentation seems to be fear mongering: awaken people to the ill effects of their high dietary sugar consumption, and they will be so disgusted with their habits that they will never again touch a can of soda or a candy bar. The colors of the graphic – red, black, white and gray – and some of the typology evoke Coca-Cola, which helps drive home the point about soda’s contribution of sugar to the American diet. I think the graphic is effective in conveying a sense that the American diet is too high in added sugar, which is certainly true: 13% of calories in the American diet come from added sugars, which is significantly higher than the amount from every authoritative organization (USDA, WHO, etc). However, in terms of behavior change impact on the intended audience, the graphic seems relatively ineffective. First, the intended audience probably does not consume high levels of sugar, so it doesn’t make sense to target them as a population that needs to cut down on sugar intake. Second, some of the illustrations meant to shock the reader are over-exaggerated and nonsensical (i.e. in one lifetime we eat the amount of sugar in 1,767,900 Skittles), and end up conveying very little substantive information.

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Use of Non-medical Adderall

“College Students Aren’t The Only Ones Abusing Adderall”

This article focuses on non-medical Adderall use, a drug that is believed to frequent college campuses everywhere to keep students more focused while studying. But title implies that it isn’t only frequently used on college campuses like some articles in the news will lead you to believe. In fact, we learn that Adderall is used across many ages. This article is looking to inform a wide range of adults about who is actually using non-medical Adderall most frequently and how that compares to the perception that college student are the biggest abuser.


The first visual aid is a simple bar chart that compares different ages to the used of non-medical Adderall. But it also separates college students from their counterparts in the most common age bracket for college students, 18-22. While we might note that college students age 18-22 do have the highest percentage use of non-medical Adderall at over 14%, we can clearly tell that they are closely followed by 3 other groups that all have more than 10% use. Although this graphic is simple it is effective in showing the all-around use of this drug because it requires little additional explanation to understand the graph.


adderal-collegesLater in the article, there is a comparison to selectivity of the school to non-medical Adderall use, shown by the second visual aid. We can see a clear positive correlation, as the school gets more selective the percentage of students using increases. And a few schools are highlighted to show where they fall on the graph. This graphic is not very effective; the four selected schools seem as though they were chosen at random,  and I don’t think the graph accurately portrays what the rest of the article is trying to say. The graph alone would lead you to believe that the brightest of college students frequent Adderall most often to succeed, but from the reading we learn that it tends to be the students with lower GPAs at their respective college that abuse Adderall.

WSJ World News Data Viz Review

A Divided Libya Struggles Against Islamic State Attacks [Source]

In a recent Wall Street Journal piece about Libya, oil, and the Islamic state, there are two interesting data visualizations. They are both related to the same story, but I will address their merits individually. The first chart, Hot Spots, is very strong. However the story’s second chart is less than ideal.

Hot Spots

Screen Shot 2016-02-04 at 3.01.10 AMThe first visualization is of recent Islamic State attacks in Libya. This is a very strong chart in many ways. In broad-strokes, it displays the data very clearly and in simply. It adds to the reader’s understanding of the story. And it is visually pleasing without being distracting.

More specifically, the author has chosen the obvious way to show a set of locations: a 2D map. Each data point on the map, with is an attack site, is symbolically represented with a black dot surrounded by a red explosion-looking icon. The black dot shows the exact point of the site, while the red icon draws the eye towards the data.

The scale of the map is sufficient in allowing a reader to clearly distinguish the various data points. The light texture on the map’s surface gives some auxiliary information about the geographic terrain, but it does not distract or complicate things.

Since, on a global scale, the data points are relatively close together, the map is fairly zoomed in to northern Libya. However, the mini-map in the bottom left corner of the screen gives the reader context to what part of the region (northern Africa), the up-close map is focused on.

  Libyan Oil Squeeze

The second chart, which attempts to convey Libya’s hurting oil production and revenue, is much weaker.P1-BW243_LIBYAO_16U_20160203172108

oth data sets being displayed in this chart (Oil production and petroleum revenue) are quantities over time. In the left chart, time is (properly) plotted on the horizontal axis. However, in the right chart, time is plotted vertically, which adds confusion and makes it very difficult to quickly scan for trends over time.

I hypothesize that the author knew this chart was weak and did not convey a message alone, so the subtitle of the chart is a straightforward, plain text explanation of what the chart is actually trying to convey.

More than an outcome: Iowa Caucus 2016

From “Iowa Caucus Results” by Wilson Andrews, Matthew Bloch, Jeremy Bowers and Tom Giratikanon for The New York Times

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“Entire Nation Remembers Iowa Exists” is what I imagine headlines the front page of satirical news site The Onion following this week’s Iowa Presidential Caucus. As humorous as it sounds, the joke rings true for one main reason: most Americans probably don’t know much about their own state, much less a random one in 50.

But the data pulled from Iowa on February 1 is greater than winner and loser, and this hidden gem of value requires a grasp of Iowa that extends beyond what the average American knows or cares to Google search.

Questions like “Are most of Hillary’s Iowan supporters considered higher income?”, “Do Iowans in cities vote differently than those in rural areas?”, and “What does any of this mean?” are just a few examples of what the results could tell us, and what their answers offer is a greater understanding of what is happening in the 2016 Presidential Election.

The tricky mix of context, visualization, and clarity that this data demands is exactly what makes the New York Times “Iowa Caucus Results” so brilliant.

In sixteen images and succinct descriptions, the publication manages to illustrate the results of the Iowa Caucus with key factors in mind: population, income, religion (Republicans), age (Democrats), and comparison to previous presidential elections. From here, readers can see which candidates came out on top with these considerations in mind. Percentages give clear presentation, while circles corresponding in size to share of the total percentage and in color to the candidates illustrate the data in a visually appealing way. If the New York Times’s goal was to breakdown the Iowa Caucus results in a captivating, approachable and educational format, they succeed.

Of course, to the New York Times audience, this sort of analysis isn’t new– it’s expected. Their national audience consists mostly of well-educated, middle-aged, relatively well-off readers who can follow these sort of graphics with ease. However, the beauty of data is that with the right communication, it may challenge readers on their preconceived ideas. This presentation leaves the truth of the numbers clear. For example, as a college student witnessing the rise of Bernie Sanders across teenage social media, I expected that Bernie Sanders won college students by a landslide on Monday night, but the graphic clearly tells me this is not the case. If Bernie Sanders were my candidate of choice, this might prompt me to take up campaigning for Bernie Sanders among my fellow college students–to act. Even if he weren’t my candidate of choice, this realization begs analysis, thought and even more questions (“Why?” being one, for example).

Simply put, this presentation works.

Hopefully, we won’t forget Iowa before the 2020 caucus comes around. But hey–if we do, at least we can count on the New York Times to fill us in.

Cell Phones and the Bathroom

phones and bathroom

Cell Phones and the Bathroom is a poster that illustrates the unknown facts about people using their cell phones in the bathroom. The general audience of this poster is anyone who uses a cell phone on a daily basis. The point of this poster is to discourage people from using their phones while they’re in the restroom. It talks about how many people admit to using their phones while in the restroom, while implying that because of this fact, poop can be found on some phones. This poster is organized into two main sections. The top section discusses the three statistics that most people would probably find horrifying. These statistics are highlighted by using larger text and darker font color. The bottom section delves deeper into what people actual do when they use their phones in the restroom. Each activity listed is followed by the percent of people who say they have performed each activity while in the restroom.

I think the poster overall does a decent job at getting the point across since I immediately had the reaction the poster wanted. However, there was one point in the poster that initially made me confused. Similar to the example we discussed in class, the percentages in the bottom section of the poster are misleading. At first I thought the percentages were in reference to how much time is spent on each activity, not what percent of people has done the activity. I think the right choice was made with the fact to put on the top. Knowing that 1 in 6 phones have traces of poop on them is a shocking fact that will convince many people to not use their phones in the restroom.

Gasoline Affordability by Country

Bloomberg created a data presentation titled “The Real Cost of Filling Up: Gasoline Prices by Country,” which includes data on gas prices, gas consumption, and income. Each country is represented by a line ranked in three ways: the numeric gas price, the gas price as a fraction of a day’s wage, and the fraction of income spent on gasoline. This visualization is designed for Bloomberg readers interested in global economics and gas prices. This is reasonable, given that Bloomberg mainly deals with economics and business.

US Gas Prices India Gas Prices

The goal of this data presentation is to represent worldwide gas prices in a different light, which highlights the global differences in the affordability of gas. Simply comparing raw gas prices tells one story, but comparing the fraction of a day’s wage required to buy a gallon of gas tells another story. For example, according to the graphic, gas was $2.74/gallon in the US and $3.95/gallon in India. This makes it seem that gas in India is quite affordable. However, a gallon of gas costs less than 2% of a day’s wage in the US, while it costs almost 80% of a day’s wage in India. This comparison gives a drastically different picture.

I think that this visualization is somewhat effective, but can be better. I like that the visualization portrays multiple ways of comparing gas prices across countries. However, it is significantly lacking in that it takes quite a bit of time and effort to get the most out of this visualization. Since the labels for at most two countries can be highlighted at one time, a substantial amount of clicking around is required to compare more than two countries.

Global Carbon Dioxide Emissions: Causes and Solutions

Link to Data Presentation


Paulina Urbanska’s striking 2011 data visualization of the causes and solutions to carbon dioxide emissions is ambitious but imperfect. The represented datasets are clearly labeled on the top ‘axis’. There is a mix of quantitative and qualitative data for the causes and effects. These include CO2 emissions by continents/countries and proposed solutions accompanied by the potential carbon dioxide savings per inhabitant. This visualization is arguably intended for a typical educated adult civilian, as evidenced by the balance of mild technical jargon such as ‘photosynthesis’ and ‘acid rain’ with humbly practical solutions that include turning off lights at night.

By framing the issue on a per-inhabitant rather than global basis, the presentation is a personal call to action to reduce one’s CO2 footprint by following some of the solutions. Clear, bold visual cues such as line thickness and font size highlight continents and countries that produce a disproportionately high amount of emissions, as well as particularly impactful solutions. However, between the two colored flows, which are informative on their own, is a list of pollution effects that does not visually connect to either flow sub-visualization. A potential connection between them that could have been highlighted is the particular countries for which the solutions are most relevant. For example, the recommendation to reduce car speed would be more applicable to the car-dense United States than Algeria. As it stands, the two colored flows are not well linked story-wise, which impairs the effectiveness of an otherwise informative and visually compelling data presentation.