Beat the T! Biking Toward a Healthier Boston

Julia Appel, Iris Fung, Eric Lau

The data says that in Boston, more than 30% of work commuters depend on the T to get to work and that biking is a faster and healthier way to do it. Within city limits, biking often saves time when compared to the T. Furthermore, bike commuting helps Bostonians stay healthy and active, adding up to 50 minutes/day of moderate to vigorous activity with an average round-trip commute. Bikers can burn almost 400 calories per day this way! Still, only 1.9% of Bostonians commute to work by bike. We want to tell this story to encourage more people to reevaluate their commuting options, by creating an intervention in their daily routine encouraging them to bike – for their time and health.

To that end, we propose an interactive data game that is commissioned as a joint venture by the Boston Public Health Commission, Hubway system, and Massachusetts Bay Transportation Authority (MBTA). A stationary bike that looks like a Hubway bike will be installed onto various T station platforms.When the user begins pedaling, the game begins on the large screen in front of the stationary bike. For the purposes of this prototype, we are assuming that this bike is installed in the Brigham Circle T station and the user has chosen the Museum of Fine Arts, two stations along the E extension of the Green Line.

Our audience is the regular MBTA Green Line commuters who have not yet seriously considered other commuting options and may not even be aware of those available to them. The Green Line, in particular, is notorious for late trains, weather delays, and unexpected breakdowns. Furthermore, the Green Line covers areas that are easily bikeable, especially further away from the city. We envision a commuter standing on the station, with some time to kill as they are waiting for their train to arrive. The explicit invitations from the screen and implicit invitations from the empty bike seat entice the person to hop onto the stationary bike. They would then play the game, which would automatically start as they pedal. As they play, facts about biking, the T, and public health appear on the top-left corner of the screen, engaging not just the participant but also the surrounding audience. The data is drawn from a variety of sources, including the suggested Hubway 2011-2013 dataset; and annual statistics from the MBTA (2014 Ridership and Service Statistics) and National Institutes of Health. At the end, the benefits of biking are strongly emphasized by the fact that players are able to “arrive” at the destination station faster than if they had taken the T!

Our goals are to provide an immersive and informative experience to persuade people to reevaluate their own method of commuting and switch to biking for increased efficiency and fitness if it makes sense. We would like to ease their transition to becoming a Hubway member if they so choose. We have designed a receipt that will be printed out at the end of the game, with a code for a free Hubway ride if the player wins the game (i.e. beats the T). At that point, by choosing to hop onto the bike at the station to try and beat the T, the participant has already engaged in healthful, vigorous physical activity. Furthermore, with the receipt “reward” from the kiosk, they have a gratifying, persistent encouragement to become a Hubway member, speed up their daily commutes, and join the Hubway community in biking towards a healthier lifestyle for themselves and Boston as a whole.

So, can you beat the T?

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Raising the Minimum Wage: Better Finances, Better Food, and Better Lives

Judy Chang, Iris Fung, Maddie Kim, Eric Lau

The data say that over 580,000 citizens in Massachusetts – equivalent to nearly the entire population of Boston – are making around the minimum wage. We want to tell this story because minimum wage earners need over double that to fully support their families; an increase in the minimum wage is needed by constituents and food aid organizations alike to sustainably reverse hunger.

Project Bread was founded in Massachusetts in 1974. Their anti-hunger efforts now include providing food coupons, running a counseling FoodSource hotline, and supporting school breakfast programs. To augment their efforts to sustainably reverse hunger, Project Bread urges constituents to advocate for legislation to increase the minimum wage. Our audience is voters, both in Massachusetts and nationwide, who might be unaware or unfamiliar of the issue, its scale, and its impact.

Our goals are two-fold: we wish to inform voters and use the power of pathos to compel them to take action and support legislation. We saw the personal story as the perfect vehicle to achieve this. We selected a story from Project Bread’s 2013 Annual Status Report on Hunger about Sam and his girlfriend and daughter, their financial and food insecurity struggles, and Project Bread’s assistance to them. To emphasize the relatable, narrative aspect of Sam’s story, it is told through a video displaying a progression of hand-drawn pictures while Sam is narrating. The viewer can connect to Sam’s struggles through his stream-of-consciousness.

Not only can viewers personally identify and connect with Sam’s story, but they can also absorb key information on the issue and act on it very easily. While the video is playing, key facts and statistics from Project Bread and the Massachusetts Budget and Policy Center are shown on the side of the video as Sam introduces them in the video. They remain displayed for easy viewing and visual reinforcement of the video’s message. At the conclusion of the video, a button appears that directs to the signup page for Fight For 15, a political campaign advocating for a higher minimum wage. For viewers, this bridges the gap from understanding the issue at a personal level to acting on what they’ve learned in a positive way.

Watch the video here!

#NeverTrump: The Candidates are On Board, but What About the SuperPACs?

By Judy Chang, Iris Fung, and Eric Lau

The data say that SuperPACs supporting non-Trump candidates are more interested in attacking other non-Trump candidates than Donald Trump. We want to tell this story because it stands in stark contrast to the #NeverTrump movement.

The news is dominated by the 2016 election, specifically by the negativity of the candidates’ campaigns. One of the chief contributors to this negativity are SuperPACs, which wield unlimited political spending power in support of their favored candidate. We focused on exploring the data behind the SuperPAC efforts directed against Republican front-runner Donald Trump. So far, Trump has been the focus of concerted verbal attacks by Marco Rubio and Ted Cruz in the televised debates. However, after exploring the Political TV Ad Archive’s dataset in Tableau, we found that this did not hold true in SuperPAC advertising. For example, the majority of the ‘con’ ads were purchased against Rubio and sponsored by Right to Rise, a SuperPAC supporting Jeb Bush. This was surprising. For all the talk of the Republican establishment’s dislike of Trump, the data suggested that there was even more internal discord among themselves.

We wanted to express this disconnect between the aforementioned intent and execution in an intuitive way. To do this, we built a hybrid infographic/interactive chart/article. Text snippets guide the viewer. A smaller bar graph shows current delegate numbers from the Associated Press. This recognizable, friendly graphic eases the viewer into a more technical chord diagram, which is not a commonly seen chart format and requires the reader to spend more time on it to understand the relevant relationships. We chose the chord diagram over a normal bar graph, because the directional arrows and arrangement of candidates around the circle connoted the feisty conflict of the campaign. Our infographic article combines humor and data to give the reader a non-obvious insight on the Republican race.

Check it out here!

Activity Log of Data Created on Saturday, 2/6/16 – Eric Lau

I took Saturday off to cook food but still generated a wide variety of data.

  • Query, temporal, and text data of my online actions on the Google platform: checked, cleaned out, and sent email via Gmail; watched some videos on YouTube; used Google Search; and recorded this list on a Google doc.
  • Address data for grocery delivery by Peapod: attempted to buy groceries online through the Peapod website (before realizing I needed them today, not tomorrow).
  • Fare transaction data for the MBTA: took the 1 Bus to and from Shaw’s/Star Market.
  • Coupon selection history data for coupons.com: Looked at coupons for good deals while on the bus.
  • (Inadvertent) picture data for Snapchat: Was very likely captured in photos when the person in front of me on the bus decided to take Snapchat selfies that included everyone behind her.
  • Music history data for Apple Music: Listened to a mix of old and new songs on the bus.
  • Credit card financial data: Paid for groceries at Shaw’s/Star Market.
  • Time and location access data for my MIT ID: Tapped ID to get back into Burton Conner.
  • SMS/iMessage data: Sent texts to friends and family throughout the day.
  • Call detail record data: Generated for Verizon when I called my sister in the afternoon.

Global Carbon Dioxide Emissions: Causes and Solutions

Link to Data Presentation

CO2_EMISSION

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.