Rescue Food, Provide Meals

Team: Almaha Almalki / Christian Feld / Erick Friis / Sam Resnick

The Food for Free dataset leads us to three interesting conclusions:

  1. The sheer amount of food that is produced, stored, and then subsequently dumped in the Boston area alone is massive.
  2. The Food for Free organisation is creating a large impact by simply rerouting that food to become meals for the hungry
  3. Still, so many more people in the Boston area suffer from food insecurity.

We wanted to package those three findings in a compelling story that includes a call to action to help Food for Free. The format we chose is a short video with one clear message: Support Food for Free in their mission to provide more people in need with food. Our target audience is people who shop in supermarkets who could be compelled to tell their supermarket to participate in Food for Free. These people would likely have an interest in social issues and would be looking for ways to make a difference. Our thought was to publish this video in a social media setting. Because of this, we decided to make sure that the basic message could come across in a short time period. The graphic nature of the video would draw in the viewer, then the minimal narration would send the message home. We decided to narrate the video in our sketch presentation, but in our social media version, we would include subtitles with the narration so viewers would not need volume.

To make it a personal story we use establish a central symbol: the plate. One plate,one meal, helping one person. We calculated that every 15 seconds Food for Free rescues an amount of food equivalent to one meal. We illustrate this time span by turning the plate into a ticker.

In second step we show that in those 15 seconds Food For Free can provide a meal for one person, however there are far more people being left hungry. Every second, 8 people are left hungry in the Boston area. As the ticker progresses around a second time, these people appear surrounding it. When the plate is completed, one of the people turns green, symbolizing one person that food for free has fed. It is clear from this that Food for Free is making a difference, but that there is much need for help. That is where the call to action comes in. By providing the audience with the link to the website at the end of the video, they are prompted to click on it and would be greeted with different ways in which they could help.

You can view our (silent) sketch below.

The Choking Effects of CO2

Team Members: Almaha Almalki, Krithi Chandrakasan, Erick Friis, Aina Martinez Zurita

Our analysis of data in the World Bank CO2 emissions dataset showed a clear increase in the level of emissions around the world between the years 1990 and 2013. During this time frame worldwide emissions doubled with five countries responsible for over half of total global emissions. Additionally, to highlight the real impact of these rising emissions on society we integrated data showing a positive relationship between CO2 emissions and asthma rates. Between 1990 and 2013 asthma prevalence increased from 4.3 to 8.4%.

Our goal is to raise awareness about the harmful effects on human health that have come about as a result of increased CO2 emissions. We decided to present our data using a short video showing an arm reaching out and gradually choking a person as total C02 emissions rose around the world. The sleeve of the arm splits the emissions of the US, China, and the rest of the world. The width of the boxes change dimension to convey how their emissions have varied over time. We use captions above the arm to narrate the story with key dates and to tie in the important relationship with increased asthma rates.

Our sketch is targeting a general audience, as this is an issue that has the potential to affect all of us. The video with our data is purposely short and to the point, as it is intended to be shared in social media and understood even if the sound is off. While the video is somewhat humorous, the asthma data together with the image of suffocation sends a powerful message. We expect the audience to come away contemplating the impact of rising emissions.

Erick’s Data Log for Saturday 2/11/17

My Google Maps timeline for Saturday (gathered by Google app for iPhone). You can see if your smartphone collects this data on you at

As a technology user, I generate mountains of data every day (often without realizing it). In this post, I will catalog all of the data that I manually generated, as well as the portion of automatically-generated data that I am aware of.

Time My Action Data Collected
Throughout Day (every few minutes) Having Google App on iPhone GPS location
Throughout Day Having Apple Health App on iPhone, using iPhone as alarm Number of steps, distance walked, number of stairs climbed, time asleep (viewable in health app)
Throughout Day Sending/Viewing Messages and Emails (usually from iPhone) Email contents, timestamps, location where I sent it from, read receipts
Throughout Day Google Searches, Web Use Search/Browsing History, Clicks (primarily Google/Facebook for Ad targeting)
9:30am, 10:00am Told Alexa (Voice Assistant) to turn on/off the lights and play/stop Phoenix Radio on Pandora Voice print info and requests (Amazon), station played and specific songs played (Pandora)
11:55am-12:20pm Took an UberPOOL Timestamped route, price, and passenger rating (Uber), money spent (Visa/Bank of America)
12:20pm-12:40pm Lunch at Manoa Poke Shop Order info, card info
12:40pm-2:59pm Working in Google Docs and accounting in Wave All edits (Google Docs), data export request (Bank of America), imported data (Wave Accounting), all annotations (Wave), usage logs (Apple Laptop)
2:59pm-3:18pm Ordered UberX Timestamped route, price, and passenger rating (Uber), money spent (Visa/Bank of America)
3:18pm-4:39pm Got Coffee with a Friend in Boston Security footage in shop, Payment
4:40pm-5:05pm Took MBTA Green Line from Park Street Station CharlieCard Used at station (MBTA)
Night Working on Computer More tracking from Google (Docs, Chrome, Search, Inbox), Pandora music listening, taking handwritten notes on Samsung tablet (automatically uploaded to Dropbox)

Now all this data begs the question: How is it used? Letting You Interact with Sea Freight

This past IAP, I worked in the new data science group at Maersk Line, the biggest shipping company in the world. One of my coworkers found, which lets you interact with GPS timeseries data for cargo ships in 2012.

I enjoyed this data representation because it conveys many complexities of global trade without overwhelming its audience: the general internet-using population. On my first glance, the site displayed an aesthetically pleasing bathymetric map that showed global ship movements. However, more aspects quickly began to show through. I zoomed in on choke points, such as the Egyptian Suez Canal, the Panama Canal, and even the area around Singapore. The busiest world ports glowed, which actually helped inform my forecasting work the next week. Even unrelated facts such as the Earth’s curvature show in the ship movement–look at the route from the Vancouver to East Asia. The toggles also allow you to view different cargo types, CO2 emmissions, etc., so I feel like I always learn something new when I visit.

Even though this visualization displays fairly raw data, it does a great job of entertaining and informing: what I perceive to be its two main goals. The map’s interactivity entertains users by letting them discover their own inferences, and the map provides a natural way to deeper explore these inferences. These personal conclusions result in a much higher-impact experience than simply seeing charts showing CO2 emissions, cargo flows, etc. The inferences bring the user into the data, personally connecting them to the data’s story.