The data says that the bee population is on the decline and this has a larger effect than just the cost of honey. We wanted to tell this story because many people are aware that the bee population is declining, but they lack the “so what”, and can be unsure of how to help the situation. According to FOX news, “The honey bee contributes to a third of the country’s food supply”. This comes mainly in the forms of fresh fruits and vegetables.
For our data visualization, we used the historical bee data to create a simple, yet powerful map. The map displays outlines of the states which currently (2017) have 60% or more of their pre-crisis populations. Based on research we determined the bees were at healthy rate in 1990, thus we used the historical data from 1990 to calculate the population differences.
We envision our map being the attention grabbing sign for an activist group at a farmer’s market. The data visualization will have a titled overlaid asking “Is your state on this map?” This will intrigue shoppers at the farmer’s market to come to the booth. At the booth bee care packages will be handed out. Included in these packages are items that can help individuals do their part to improve the bee population. There will be seeds, bee-friendly local honey, a water basin, and information on how to take further measures.
We believe the farmer’s market will be an effective place for our visualizations because the audience, farmer’s market shoppers, are primed to care about the bee crisis. Without bees to pollinate produce, the fresh fruits and vegetables found at a farmer’s market would cease to exist.
Shopper that were aware of the bee crisis would welcome the bee kit and further information on how to help. Though, if shoppers were unaware of the importance of bees, they will be drawn in by the visualization and learn about the connection. They will have an interest, because as farmer’s market shoppers, they already enjoy the benefits of bees.
This is a summary of types of data I created and were captured in digital form on 5/1.
At 9 AM I wake up to my phone’s alarm. I briefly check my e-mail before heading downstairs to grab some breakfast. Already I am creating data: by using Google chrome on my phone several entities are tracking my behavior. Google is logging my behavior due to using Chrome, MIT because I am connected to their routers and checking their e-mail servers. We could go further and say MIT’s ISP, DNS servers, etc. are also logging data but at that point they don’t know the data is me, Lawrence Sun, browsing the internet.
At breakfast I swipe my ID at the registrar. This is logged by MIT’s techcash and dining services. While eating, I catch up on various things on my phone. Reddit, Gmail, Quora, and the New York Times are all logging data about my visit.
I leave my dorm for class. Because I am now moving with my phone, Google is tracking my location with my phone’s GPS.
After class, I get a burrito at Anna’s and I pay for it with my credit card. Both Anna’s accounting services and my bank (Bank of America) log this transaction.
I then go to my afternoon class. I open my laptop and start browsing the course website; it is hosted by CSAIL and the course notes are being hosted by NB. Both CSAIL and NB are logging my behavior.
After my classes are over, I return back to my dorm and stay off the grid for a few hours. Dinner time comes around and again I swipe my ID and my meal is logged. After dinner, I work on some work for my classes. I need to read a paper for one of my courses so I visit arXiv to retrieve the paper. After I finish reading the paper, I submit answers to some questions to an MIT PDOS website. Both arXiv and PDOS are logging my activity. After this I visit MIT Stellar to browse the upcoming homework for another one of my classes. Finally, I am left writing this blog post, leaving another data footprint at WordPress in this case.
I was reading about the recent selling of IPv4 addresses by MIT to Amazon and in some of the discussion a rather old but classic data visualization popped up:
This is, of course, the xkcd “map of the internet”. The data that is being shown is which entities own certain IP address ranges: essentially blocks of the internet. For example, in the data visualization we see that MIT owns IP prefixes that start with 18.
The audience of this is the same as the usual audience to xkcd, which is very broadly speaking nerds on the internet. The goal of the presentation I think is to show that relatively few players control the whole internet; you’d think that with there being over 4 billion possible IP addresses there would be a lot of freedom but in reality there are only around 100-200 players who own everything and license out IPs to others.
I think the visualization is effective given the target audience. To a general person, this is probably too cluttered because so much data is being shown. However, as xkcd viewers are generally “nerdier”, they will be willing to spend more time to investigate and thus that issue wouldn’t immediately discredit the visualization. The fractal mapping explained at the bottom is an efficient way to compress the previously 256 data points to a 16 x 16 square while still keeping contiguous regions together (so for example, the blocks Europe owns are all grouped together) which greatly enhance readability given the constraints they’re working with. Probably the only glaring flaw I’d say is this is outdated; this was made 11 years ago and the IP address layout has changed quite a bit, so it shouldn’t really be used as a discussion point today anymore. However, in its time I think it did a great job given the target audience and the data it wanted to present.
by Margaret Tian, Tony Zeng, Tina Quach, Willie Zhu
The data says that sea ice cover in the Arctic is declining year-over-year. Declining sea ice is a major factor in the decline in polar bear populations because they primarily hunt on the ice. Thus, melting ice caps reduce polar bears’ ability to feed themselves and raise their children. From 2001 to 2010, polar bear populations have dropped by 40%. We want to tell this story because as a young child, you may hear about global warming, but not really know what it means or why it’s so bad. Even if you already associate melting ice caps with sad polar bears, do you really know what that looks like?
Our audience is 8 – 11 year olds who like animals and have yet to learn about the impact global warming has on their animals. Our goal is to use the specific example of melting ice caps and polar bears to teach these kids about how global warming hurts the animals they love. We accomplish this, through our design of a physical, Candy Land-inspired board game, Polar Bear and Glaciers: Seal Your Survival.
We used Arctic sea ice data to determine the amount of ice cover for each time period corresponding to each stage of the game. In particular, we looked at the amount of ice cover in the Bering Strait in 2012, 2014, and 2016. As the amount of ice decreases in the real world, the amount of ice in the game decreases proportionally. This is intended to mirror the struggle that polar bears have in the real world due to sea ice loss by increasing the difficulty of the game.
Our physical board game is an effective way to tell this story because it is a physically engaging, social way to collectively empathize and learn about the polar bears and their struggle for survival. Each player is put into the shoes of a polar bear that needs to eat at least 8 seals in order to survive the year, reflecting the real amount a polar bear needs to survive. As the players progress through the game, they discover how it gets harder to get the seals as the proportion of water to ice increases (See Game Rules here).
Team members: Paul Choi, Miguel Garrido, Lawrence Sun, Kimberly Yu
The data say that different car models have different fuel economy levels, and the driving speed also affects how fuel efficient the car is. We want to tell this story because fuel efficiency is determined by so much more than just the type of car you drive. Most people are aware that certain cars (e.g. Prius) are more fuel-efficient than other cars (e.g. Ford). However, not everyone is aware that when you drive a car at a speed faster than its optimal speed, the car’s gas mileage decreases, more greenhouse gases are produced, and you end up wasting gas and money. Our audience is car buyers and drivers, and our goals are to teach participants about fuel efficiency for different cars at various speeds, and help them make better driving choices.
Our participatory data game is a digital multiplayer game where the goal is to reach the destination in the least amount of time while spending the least amount of money. Players are given 5 gallons of gas per round, and each gallon costs $3. Each round, a player chooses 1) a car model from four options (or keeping their current car) and 2) speed (ranging from 30 mph to 90 mph). After each round, the player’s balance is updated, and the player’s car animates across the screen to reflect the distance traveled and its speed. For each subsequent round, the player can choose to keep the car or choose a different car. A timer keeps track of how long it takes the player to travel 1000 miles, and the amount of money the player has spent is displayed. At the end of the game, a weighted total score is displayed. Choosing the type of car and the speed while attempting to reach a destination within a time limit helps the player discover and learn that the type of car and the speed both affect fuel efficiency, and there is a tradeoff between time and money spent.
We based our data game off of the US Fuel Economy measurements and the MPG for Speed Calculator. Given the MPG values for vehicle models from the 2017 Fuel Economy guide, the MPG for Speed calculator helped us calculate the cost, distance driven, and driving time for each round in the game. The higher the MPG, the more fuel-efficient a car is, and the less greenhouse gas emissions the car will produce. However, if a car is driven faster than its optimal speed, the car becomes less efficient because the air resistance increases. We envision this game being incorporated into websites for car manufacturers, especially those that produce cars with high fuel efficiency, or at car dealerships. Car manufacturers can use this game to playfully inform customers about how fuel-efficient their car is compared to other cars. Car dealers can use this game to help customers make better decisions as well as make waiting time more exciting and beneficial.
Team: Almaha Almalki, Mikayla Murphy, Ashley Wang, and Jingxian Zhang
The dataset we focused on was the US Fuel Economy Measurements. We noticed that fuel economy is not only related to vehicle classes but also to drivers’ driving habits, and found a list of tips and trips to improve fuel efficiency. We hope to tell a story about how driving habits and advanced vehicle technologies can improve fuel efficiency. Our target audience are car owners who want to save money in fuel efficiency. Our goal is to present players some knowledge about fuel efficiency (especially for vehicles they own) and how good their driving habits are.
The game will be on a racing arcade machine where players can have physical driving simulation. The screen is also a touch screen for all the digital interaction (Figure 1). In the game, players will be asked to finish a task, e.g. going to grocery store, in a route they select (city, highway, interstate). To win the game, they should try to reach higher fuel efficiency. Players start the game by choosing a vehicle and choosing a route (Figure 2). Then, they will answer some questions for the vehicle set up, such as whether to enable start-stop system and whether to take the canoe off the vehicle.
When en route, the game will monitor players’ driving habits such as whether they exceed speed limit and whether there are hard acceleration and braking. At the end of the game, players will receive their race result and their personal driving profile, which they can print out or share on social media (Figure 3). In the handout, players are shown how their driving habits and vehicle setup affects the money they can save on fuel and how to improve their fuel efficiency. By playing the game, players can actually relate their driving habits to the accurate amount of money they can save, and the driving personality in the profile can be a fun way for them to know how they drive and what to improve.
By Nikki Waghani, Sean Soni, Sharlene Chiu, Margaret Yu
The data say that different cars get vastly different mileage, and mileage also varies from highway to city driving. We want to tell this story because we want to educate consumers on the difference between cars and styles of driving when it comes to gas mileage. Thus we have created a choose your own adventure game where the choice of car at the onset affects how the scenarios play out, with an emphasis on gas mileage, and a goal of acquiring “likes” along the way. Our audience is specifically young professionals who are thinking about buying a BMW. We plan to place our game in a kiosk in BMW dealerships. Our goals are to educate consumers about their choices, and encourage consumers to buy more fuel-efficient cars in order to help BMW meet government requirements regarding the average fuel efficiency of their fleet.
Our data is sourced from the 2016 information at fueleconomy.gov, and is the result of testing done by the EPA as well as by vehicle manufacturers with oversight from the EPA. Using this data, we’ve designed a quick, easy, and fun way for someone entering a dealership to learn about the brand’s cars while figuring out what might best suit their needs. The goal is not to sell a particular car – this would be impossible as each person’s needs are very different – we will, however, help them learn the differences between a brand’s numerous cars without feeling overwhelmed. In order to encourage the customer to play multiple rounds of this game with different cars, our kiosk will print out a coupon for free add-ons (such as window tint or undercoating) each time the game is played. By playing multiple rounds of this game, the customer will get a feel for how much money they can save by buying a more fuel-efficient electric or hybrid car, and what some of the potential tradeoffs may be. Our game also integrates educational facts into the game, such as the fact that fuel economy is better on the highway than in the city, and going above 60mph on the highway reduces fuel economy. This game is much more effective than simply presenting fuel economy data, as it allows the consumer to interact with the data rather than just read it.
Global warming is inevitable, but if we play the game right, the results won’t be as catastrophic.
My data game is a modified version of Jenga. There are 3 stakeholders; environmentalists (pink pieces), politicians (green pieces), and human factors (representing fossil fuel companies, etc) . While staying in the confines of their roles, the players want to prevent the tower from falling as long as possible.
Each round, the factors player must remove any tile.
The politician player must remove or move one green tile each round.
The environmentalist can remove or move one tile every other round. Every other round they may add to the tower at their discretion. The environmentalist starts with 3 extra pink tiles to do this.
What these rules represent…
The factors player represents the human factors constantly adding instability to the system. It is the job of the other two players to counteract this.
While politicians have a lot of power, they can’t change the system completely by performing additions. Also they are confined to moves that are dictated by their constituents and party (they can only move the green tiles). Therefore, their stabilizing effort is very slow and, could be, destructive.
While environmentalists have the power and knowledge to do good and help the system, this is slowed down by politics and destructive human factors. Furthermore, they have less influence than corporations or politicians, and therefore less tiles.
The first surface level learning comes from the pieces themselves, which all have different facts on them. The environmentalist tiles also have suggestions on them.
However the deeper level is understanding how these role confines actually represent the current system and the issues within it.
Team Members: Erick Friis, Krithi Chandrakasan, Aina Martinez Zurita, Sam Resnick
The US fuel economy measurement dataset shows many surprising and non intuitive values for different car models. We want to tell this story, because we believe there is a disparity between perceived and actual fuel economy among car owners.
For our participatory data game we designed an interactive visual game on a mall display board that allows users to guess the relative efficiency of their car and compare this prediction with the true efficiency. The game initially prompts users to enter a prediction with the question “How efficient is your car?” and then allows them to input the make and model of their specific car to determine the accuracy of the prediction. Users will have to walk around to the other side of the kiosk to view the results creating an element of suspense. In addition to showing the disparity between the prediction and reality the game will also display similar vehicles that are more fuel efficient. This data will aggregate over many user interactions and will show the greyed out predictions of other users. This will create a graphic that is developed in real time and grows over the course of the day.
Our target audience for the game is individuals who go to malls, typically middle to upper class Americans. While more progressive and environmentally motivated individuals are likely to participate, we envision more widespread participation due to the unique and interactive aspects of the game. The game is applicable to both people with average incomes who drive vehicles like the Toyota Camry, and wealthier individuals who drive luxury cars like the Mercedes G550. The participatory data game caters itself to the needs and desires of the particular user, based on what car they enter. If they enter an average family vehicle, the system shows alternatives with similar safety rating, but if they pick a luxury or sports car, the system shows vehicles with similar horsepower. The choice of a mall kiosk was especially important, as they are often located at high traffic locations and have great visibility to consumers. Additionally, malls are typically located in suburbs where the primary mode of transportation is a car – think Long Island.
Our goals are to show that individuals generally believe they are more “green” than they are in actuality, as well as to motivate individuals to be more conscious of fuel efficiency and emissions when purchasing their next vehicle. Our interactive game does a great job of accomplishing the first goal by showing real time data on beliefs that are collected from many consumers at the mall. The second goal is accomplished with the call to action prompting users to be more conscious while also giving them specific vehicles to consider when making their next purchase.
Team: Autumn Jing / Brandon Levy / Christian Feld / Kevin Zhang
We explored MASIE-NH which stands for the Multisensor Analyzed Sea Ice Extent – Northern Hemisphere. The data says that the Arctic is in peril as the ice cover has shrunk significantly over the last decade. We want to tell this story because losing the Arctic sea ice will result in very real consequences, from an increased number of life-threatening severe weather events to a positive feedback loop which will accelerate global warming, further destabilizing arid regions such as the Middle East.
We looked at data showing the daily extent of sea ice in the Northern Hemisphere from 2006 through 2016. We identified the annual low-point for each year of the data; that is, the lowest amount of sea ice in a given year. We averaged these annual lows for 2006-2010 and 2011-2015 and compared those numbers to one another and to the 2016 low-point. The 2011-2015 average low-point was 93% of the 2006-2010 average low-point, and the 2016 low-point was 88% of the 2006-2010 average.
Our participatory game is an effective and appropriate medium for telling this story. The limbo setup attracts people because at first sight it is a fun game. The ice extent low points mentioned above are represented by limbo bars of different heights.
The more the ice has shrunk, the lower the bar. Players get a short info sign at every bar, so that they know what it stands for. At the end of the track, there is one bar flat on the floor visualizing the scenario that the sea ice might totally vanish during the summer by 2040.
Once drawn into the physical experience, it is easier to bring our message across and encourage participants to act. A future iteration of this project would guide players to a website that provides a second layer of learning for the players. This site could also show time lapses of the ice extent in specific regions of the Northern Hemisphere.
Our audience is citizens in districts whose representatives are members of the House Subcommittee on Environment and the Economy, where “H.R. 861: To terminate the Environmental Protection Agency” is currently under review (15th district of Illinois / 3rd of Mississippi / 16th and 18th of Pennsylvania / 5h and 6th of Texas / 8th of North Carolina).
Our goal is to show people in those districts one of the consequences of global climate change and motivate them to call their representatives and demand that they block H.R. 861.