2016 Data Storytelling Studio @ MIT

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

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!

Cheers,

Felipe

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 opensnow.com. It shows for each season from 2010-11 until now, what percentage of average snowfall the mountain has had. The 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.

“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.

 

Later 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.

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

“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.

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.

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.