Online discussion questions – Day 7 (Jan 28) – Data Visualization
Find a cool data visualization anywhere on the Internet (try newspaper/magazine sites such as New York Times or Technology Review).
- What are the sources of the data visualized?
- What are the key messages in these graphics?
- What kind of delivery means do the graphics adopt to deliver the messages?
21 Responses to Online discussion questions – Day 7 (Jan 28) – Data Visualization
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A visualization I found was “Mapping Poverty in America” on the The New York Times. The data used annual income to determine which areas of America are poorer from New York to Los Angeles. The visualization had darker colors for areas with a higher percentage of people who live below the poverty line and lighter colors with areas with no poverty. When looking at the New York metropolitan area, I found that areas around Newark, Bronx, and Brooklyn had high levels of poverty where some areas had more than 40% of people living below the poverty line.
I found a database from the Temple library website called ‘http://temple.policymap.com/maps’ where you can zoom in onto most counties in the country and find a plethora of data about the area. The user can pick from 10 different areas with hundreds of more discriptive areas under each. For example, you can see the amount of African-Americans in a certain district, or the median income.The delivery this database uses is different colors to show the saturation people who fall into the specific category. The darker the color, the more saturated the area is.
The visualization I found was called “What’s Cooking On Thanksgiving” and it’s from the NY Times. It displayed popular Thanksgiving food choices and how popular they are in certain areas of the United States. The purple areas reflect ones where the dish is popular, whereas the light orange areas show the areas where the dish is not popular. It also shows how a certain area of the United States compares to the average when it comes to what dishes are being served on Thanksgiving day.
I found a visual of where immigrants have settled in the U.S. based on where they came immigrated from on the NY Times website. You can look up specific countries on the map or regions to know where the highest concentration on them wound up. When a specific country is selected, they appear as dots on the map to show how the immigrated population compares to the entire population there.
http://www.nytimes.com/interactive/2010/02/01/us/budget.html
I found a info graphic displaying the 2011 federal budget from the New York Times website. The data visualized was taken from the President’s budget proposal. The info graph tries to show the different expenditures on the budget and how they will change from the previous year. The size of the boxes is proportional to the expenditure. The color of the box represents the percent change from the previous year. The info graph allows you to see which expenditures are the biggest and which are growing.
http://www.slow-journalism.com/oscars-infographic
“How to win an Oscar” is the title of an info graphic i found. It analyses every actor and actress who won an Oscar in the past. If a man has facial hair, his chances increase by 17 percent. If he has a beard, 18 percent. The actor or an actress have a greater chance if winning if they play a fictional character, are North American, play a part from present or recent past, is a soldier/lawman(male) or performer(female), participates in no sexual scenes(greater chances for men), and who doesn’t die on screen.
On the website Flowingdata.com I found a data visualization regarding spaceships and their sizes. The visualization “Spaceships drawn to scale” by molecular astrophysicist Invader Xan graphs the sizes of fiction and nonfiction spaceships known throughout history. The graph also maps whether the ship is active (black), retired (gray), in development (blue), cancelled (orange), and space stations (white). This visualization is for FYI purposes and can be informing for anyone interested in spaceships, fiction or nonfiction.
I found a data visualization of fiscal budget break even oil prices of OPEC nations. The data visualized is the price per barrel of crude oil needed to balance fiscal budgets given the individual production levels of each OPEC nation. The primary message of the visualization is the vast range of prices per barrel of oil different OPEC nations can withstand. e.g., Qatar can withstand the current low oil prices and has relatively little fear of meeting its budget. On the other hand, Iran needs oil prices well over $100 in order to balance its budget. The visualization uses an X (production) & Y ($/barrel) variable chart with countries illustrated with colored squares that vary in size given the range of prices each country can likely withstand (and still balance the budget). It also includes a dotted-line indicating the weighted-average OPEC fiscal break-even price.
Similar to the baseball map we looked at in class, Twitter built an interactive data map or NBA fans: http://mashable.com/2015/01/14/nba-fandom-map-twitter/
The data visualized in this map is the popularity of a specific NBA team within a certain county. The key messages in this graphic is to show how even though there are many different teams, typically, one from each major city, the bigger the franchise is the more dominant the team becomes. Considering that a lot of this map is covered in a purple color, which represents the LA Lakers, it showcases that many regions far from LA are dominated by this specific team than one from their own region. The interactive style of this map gives a user the ability to compare different locations and pinpoint preferences in very distinct areas.
I found an interesting data source visualized “Immigration and Jobs: Where U.S. Workers Come From” on the New York Times (available at: http://www.nytimes.com/interactive/2009/04/07/us/20090407-immigration-occupation.html?_r=0). The source describes the number of all foreign-born immigration workers from top ten countries. First, different colors help us understand the size of number by continent and where they come from. Second, the source differentiated the workers’ proportion of each foreign-born country by the size of circle so that it helps us understand which country and how many immigrant workers in the U.S. it has. Most of all, this source has a clear data collection note that it cited the number of workers from the Census Bureau’s American Community Survey via the Minnesota Population Center. Also, it can be reliable because it uses estimate number and has a margin of error. Finally, it uses world-map, table and clustered bar to visualize data clearly.
An interesting data visualization I found on the New York Times website was titled “Student Debt at Colleges and Universities Across the Nation.” (http://www.nytimes.com/interactive/2012/05/13/business/student-debt-at-colleges-and-universities.html) The graphic involves a graph with two axes, Annual cost of tuition and fees and Average graduate debt. The graph is plotted with circles that represent individual schools. The circles are color coded based on whether they are public or private. The circles are also sized according to the enrollment sizes of the schools. There is information for the years of 2004-2010, and you can press a button to watch the circles move around from year to year. Playing that shows the overall trend of both costs and graduation debt are increasing. You can also see that private schools generally cost more than public schools, but the amount of debt after graduation is not necessarily any higher. All of the data is self-reported from the schools, so it is not necessarily the most reliable.
A visulaization I found was on HIV prevelance in certain countries. I focused specifically on the United States and South Africa. The visualization was color coded whereas the red symbolized countries with a higher percentage of the population who related to HIV prevelance. Green symbolized where the lowest amounts were and yellow and orange were the in betweens. The visulzaion showed how South Africa had a much higher HIV prevelance than America. The HIV prevelance only related to .6% of the population in America while South Africa was in the red section at 17.8%.
A visualization I found was on HIV prevalence in certain countries. I focused specifically on the United States and South Africa. The visualization was color coded whereas the red symbolized countries with a higher percentage of the population who related to HIV prevalence. Green symbolized where the lowest amounts were and yellow and orange were the in between. The visualization showed how South Africa had a much higher HIV prevalence than America. The HIV prevalence only related to .6% of the population in America while South Africa was in the red section at 17.8%.
I found a graphic on bicycle theft reported to the Philadelphia Police department through Open Data Phillly. The data is displayed by a line plot comparing the number of thefts reported from April 2010 to August 2013. The graphic itself was very simple but didn’t really grab my attention right away because if its simplicity. However I could still recognize trends when looking at it. It seemed the number of theft increased during the warmer months. From this graphic I could see fairly quickly which months come with the higher risk of bicycle theft. From this information I can assume that during the warmer months, bicycles in the Philadelphia area have a higher chance of getting stolen. This data allows bicyclists to be aware of when crime is most likely to effect them and gives them the opportunity to get proper equipment to protect their bikes from getting stolen or keep them in a place that is safe or hard to access.
I found a data visualization map at http://technical.ly/philly/2015/01/16/mos-azavea-energy-benchmarking-visualizations/. The actual map is at http://visualization.phillybuildingbenchmarking.com/#/map. This map shows Philadelphia’s new bench marking map. In the map, the different circle colors represent the building type and the size of each circle represents the amount of energy used. You can see which types of building use which type of energy, electric, gas, etc.
Find a cool data visualization anywhere on the Internet (try newspaper/magazine sites such as New York Times or Technology Review).
http://www.pewresearch.org/fact-tank/2014/12/29/our-favorite-pew-research-center-data-visualizations-from-2014/
*Percent of American Population by Age Group, 1950-2060
What are the sources of the data visualized?
The data was compiled from the Pew Research Center for this data visualization.
What are the key messages in these graphics?
This shows how the overall population in America is aging, and highlights the fact that the babyboomers (which are highlighted in brown) are getting older and closer to retirement without enough younger citizens to take over and replace them. This visualization can be used to make many assumptions, like predictions of financial insecurity for social security or to understand the talent gap that is happening in many different industries.
What kind of delivery means do the graphics adopt to deliver the messages?
The visualization uses a different color, brown, to distinguish the babyboomer generation from the rest of the civilization. Also, it uses animation to show the aging of America’s population from 1950 which was the start of the babyboom era to 2060, when the last of the babyboomers are expected to die. It centers the data on a vertical axis to make it easier to compare the differences in age groups by the width of each bar.
Data Visualization Website: http://floodwatch.o-c-r.org/
This data visualization allows for the viewer to track the ads that the average person is being shown to them on a daily basis while they are online. The key message of this data visualization would be that the ads shown on someone’s computer correlates to their interest and searches on their computer. The designer of this data visualization used half circle graphic approach to convey his message to his viewers.
http://blog.threestory.com/wordpress/topics/data-visualization
This data visualization allows for one to be able identify the applications that take up the most bandwidth and that also represent the largest amount of risk. The key messages are that this visualization shows a person what applications are safest for a person to use or which pose the largest threat. The data was displayed in four different colors, and in all different sizes of circles to represent the amount of bandwidth that was being occupied.
http://www.census.gov/dataviz/visualizations/025/
This data visualization allows people to scroll up and down one of the largest interstates in america. Its show a map of the west coast and as you scroll it indicates which city you are in and how big the population is at that point. The key message is that the map shows that this interstate passes through the second most densely populated areas in the states. It uses an interactive feature, where you can scroll up and down the graph. this makes it more appealing to the user.
http://blogs.wsj.com/economics/2015/04/14/the-student-loan-problem-is-even-worse-than-official-figures-indicate/?KEYWORDS=student
This data vizualiztion allows people to view and understand the delinquency rate of current student loan borrowers. It shows a line graph that is framed by the year on the x-axis and the percent of students on the Y axis. The message here is that the delinquency rate has been steadily rising for more than a decade now.
http://www.mastersindatascience.org/wp-content/uploads/2014/03/U.S.-Gun-Deaths-1024×446.png
The picture uses data from FBI’s Unified Crime Reports and the WHO. The key message is about lives cut short by gun violence. The picture allows people to view and understand how many people are kiiled by gun in 2014.