Analysis of Data visualisation

Analysis of Data visualisation

By Jordan Evans and Jose Fagel

https://flowingdata.com/2019/03/06/women-men-timeuse/?fbclid=IwAR1xxxRT6oWuityIb3hrSSjbYXCL2k78g0889wfMvBW9dUSVTUx_x5Wvl4M

What story does it tell? 

It tells us what a working day for American men and women looks like, to see how their schedules differ from each other.

It highlights the relationships between men and women throughout daily activities and explores the journey people take throughout the day.

How does it tell it? 

By dots cyan dots representing women and orange dots representing men. Each dot represents a person, and as time moves forward on the clock it shows what the dot is currently doing.

Does it allow for different levels of interrogation that can be seen or used on the part of the reader? eg can they drill down to discover more detail? 

The dots are sorted into categories of activities but there are no other levels of information that detail what the person is specifically doing.

Are you able to create multiple stories from it? If so what are they? 

It is difficult to track one single dot for the duration of the day however you can create stories as a whole, you can see what a large number of people are doing at a specific time. For example, you can see at 5:00 am the majority of the people are sleeping but at 6:30 am there’s a lot of movement and the group splits into smaller categories by 8:00 am such as traveling, household, and work.

Also, you could read a commentary on men and women’s roles/activities. Like this snapshot at 10:57am. Which shows some disparity in activities (Household care).


https://flowingdata.com/2019/03/06/women-men-timeuse/?fbclid=IwAR1xxxRT6oWuityIb3hrSSjbYXCL2k78g0889wfMvBW9dUSVTUx_x5Wvl4M

The movements the dots take also create patterns and tell of people’s movements throughout the day. Such as dots ping-ponging back and forth from eating and drinking at certain times. Or when large clusters quickly dissolve like at the end of the workday. 

What can you say about the visual design- layout, color, typography, visualisation style? 

The visual layout and design are effective to be able to see the data flow, the typography is easy to read and laid out good. The user is given several control points to speed up and pause the motion graphic. 

What improvements would you suggest? 

The color choice for the dots could be more effective and more recognizable. If females were pink or red and men blue or green it could be easier to track the dots.

The option to highlight and track a dot could be useful so you can get to see single stories of peoples working day and routine.

Where does the data came from, and comment on it’s source.

The data was collected over the last few years from the American Time Use Survey which is located on the Bureau of Labour Statistics site.

The source of the data is very reliable as it’s a federal agency that is responsible for measuring labor market activity, working conditions, and price changes in the economy. Its mission is to collect, analyze, and disseminate essential economic information to support public and private decision making.

Lecture Pod Five

Lecture Pod Five

https://vimeo.com/177306425

Data Presentation Styles: Why use Graphs

Why do we use graphs? To make comparisons easier

There is a great range of ways to present data to achieve this goal, often graphic designers use the wrong way because of aesthetic or what’s fashionable. 

An example is the overuse of bubble charts

A chart recreated by Alberto Cairo from a Bloomberg news story, in his book “The Functional Art”

Alberto Cairo, The Functional Art, 2013

The chart shows the change in market capitalisation of various banks between 2007-2009.

The light grey bubbles represent 2007 and the dark grey bubbles represent 2009.

From this snapshot we can say over the two years their capitalisation cap decreased, all of these banks experienced a fall in their stock price.

The bubble chart is difficult to interpret figures from but looking at the same data in a bar chart it’s much easier to make a comparison and get the estimated figure.

You can make a graph wanting your audience to compare areas but they will automatically compare heights and widths. Using circles always makes us underestimate the size difference.

A ranking of different graphic approaches to compare data

Alberto Cairo, The Functional Art, 2013

Based on human visual perception, as we need to tailor the way that we show stuff. We need to understand the way human perceptions work to decide which way we’ll present data. The more accurate and easier the judgment is for your audience to make, the more likely they’ll take away the correct perception of the patterns you’re presenting.

Alberto Cairo, The Functional Art, 2013

A case of disastrous use of poorly designed charts is the Space Shuttle Challenger launch accident. 

  • Cold weather leading up to launch day at the Kennedy Space Station
  • There were discussions between NASA and the manufacturers of the booster rocket about should the shuttle be launched on a cold day.
  • The discussion was about the O-rings which sealed the sections of the booster rocket and the possibility of if they would become damaged and unsafe.
  • The booster rocket engineers made a no launch recommendation, which was their first no launch recommendation in 12 years.
  • They faxed 13 graphics to support their recommendation.
History of O-Ring Damage in Field Joints

It shows a catalogue of all the earlier launch damage to the booster seals. It’s shown in the historical launch order from 1 to 24. 

The problem is that obscures the two most important variables of interest, the relationship between temperature and the degree of damage. 

  • The temperature is shown in the nose of the rockets
  • The degree of damage is in the legend in shaded areas

The rocket engineers chose to order their information by time, that is the order of launch not be temperature or degree of damage. This makes the diagrams cluttered and any pattern difficult to see. 

Edward Tufty took that same data and redrew the rocket diagram as a starter plot graph.

Showing the relationship between temperature and O-ring damage. It reveals a clear pattern of damage and severity.

Scatter Plot of O-Ring Damage and Temperature of Field Joints

Bar Chart

Easy to use and the audience have a familiarity with them. It makes it quick to compare information and reveal highs and lows at a glance. Effective when you have numerical data across categories.

Line Chart

Connect individual numeric data points. Primary use is to display trends over a period of time.

Pie Chart

Commonly used but also very commonly misused. They are used to show the relative proportions or percentages of information. Limit the number of wedges to 6, if you need more than use a bar chart.

Reflection

In Lecture Pod Five, I learned why we use graphs as well as graphs being overused and not used properly and ultimately leading to disaster. Then the use of particular charts such as bar, line and pie charts are defined.

Visual Vocabulary

Visual Vocabulary

Designing with data

There are so many ways to visualise data – so how do we
know which one to pick? In the link use the categories across the
top of the page to decide which data relationship is most important
in your story, then look at the different types of chart
within the category to form some initial ideas about what
might work best. This list is a useful starting point for making
informative and meaningful data visualisations.