Student Time Visualisation

The story here is just how much we sleep. The visualization shown here shows just how much we actually do sleep. It is amazing. The amount of time we, as a group of 48 students over the course of a week, slept for more time than we worked, attended university study, did university study and traveled with both public and private transport. That is just insane. It shows just how vital sleep is to us.




Data Visualisation Analysis -National Flag Colours

flag colours.png

What is the story? 

This image represents the most commonly used colours on national flags around the world.

How is it being told?

A colour grid is used to display each colour. A variance in size also reflects the volume of each colours use.

The colours are grouped with similar colours to make it clearly identifiable which tones are the most popularly used.

As you can see, the main colour we see is red followed by blue/white, green, yellow, black and orange. With the subdivisions of each colour having their own hierarchy.

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?

It allows the reader to look into the basic colours, then the colour variations of the main colour groups. It can be hard to read with the colours in some areas blending together but its detail is lost as it is only colour. There isn’t any real percentage or idea on number figure of the visualisation.

Viewers must take the face value of the visual, as there is no additional information leading them to which flags each colours may be from, or what the actual percentages are etc.

No written facts or data support the visualised data.

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

Not really, the data visualisation only gives a visual representation of colour use without displaying where the colours specifically come from, number figures, differences between each country’s flag etc.

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

The layout is clean and clear. It shows us the message it needs to get across despite its lack of supporting typography. Its square layout represents 100%, although, a square to represent 100% is hard to dissect easily when there is such a variety of sections inside the square.

What improvements would you suggest?

Instead of a square to represent the whole data being displayed, a circle may have made it easier to section each colour into it, creating almost like a pie graph perhaps. If each colour had the flags, which used that colour labelled with it, may have given more dimension for readers to collect information.

Maybe even dividing each colour shade into separate graphs based on continents the flags come from etc, maybe also give a deeper dimension to the info graphic.

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

It was an award winning data visualisation project by designers Jeppe Morgenstjrne and Birger Morgenstjrne. It was taken from the UN Flag Data of all 193 countries. Coming from UN information, the data behind the info graphic must be somewhat reliable.


Morgenstjerne, J. & Morgenstjerne, B. (2016). Interesting Facts About Flag Colors And Design That You Probably Didn’t Know. Digital Synopsis. Retrieved 6 August 2016, from

Data Visualisation Analysis – Brazilian Flag


What is the story?

The Brazilian flag graphic tells the story of how money is dispersed amongst the Brazilian population in categories. It does this by using each different colour featured on the Brazilian flag to represent one statistical group of people. The green (the largest area) being people who live with ten dollars a month and the white (smallest area) being those who live with more than 100,000 dollars a month.

How is it being told?

The story is being told through the clever use of the Brazilian national flag. Each colour on the flag represents one group of people. The data visualisation is the flag. There is no bar graph of pie chart used here to show the data, only an already recognisable symbol of Brazil. The use of colour, shape and varying size is how each section is compared.

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?

No. This Data Visualisation does not allow you to interrogate it at all. Each statistic is only alluded to through the size of the area of each colour, which you cannot easily tell anyway. There are no numbers used at any point in this data visualisation.

The data visualisation is only displaying one dimension of the money figures- how it is dispersed. It does not allow different aspects of the information to be interpreted such as, what the employment rate is, where these people live in each category around brazil, etc.

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

Not really. All you can really tell from this visualisation is that there is a huge divide in the income with most being very poor.

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

Honestly, there is not much actual design involved in this visualisation. All that has been done here is to stylize the Brazilian flag to give it a little more depth and add a key to show the statistics. The small amount of type used is just a normal sans serif typeface used for body text, easy to read and simple, but it works well. The actual yellow and blue parts of the visualisation also look to be about the same size in terms of area, despite the intent to have the yellow bigger.

By using the Brazilian flag to layout each section, it does make it harder for the reader to compare as the distance is further away, the sections are dispersed into smaller sections as well.

What improvements would you suggest?

I would suggest a clearer or more organized comparison of data against each other (The visual style of the flag makes it hard to really compare the size and shape of each colour against the others when they are placed abstractly amongst each other in the shape of a flag).

Perhaps including a different dimension of information to create a stronger story about the topic. So instead of just talking about each group and how much money they live off each month, maybe also compare where around brazil majority of those people live in each money bracket.

I would also suggest the use of some actual statistics in this visualisation to give it more credibility.

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

It is doubtful that there were any actual statistics used in this visualisation at all. We could not find any actual data source cited at all throughout this visualisation or anywhere on the websites we found it. It is likely that this “data” was simply anecdotal observations used to make a point about the living conditions in Brazil. Raw statistics is not what this visualisation is about, it is about making a point.

Feedback and comments on this visual on the website we found it, commented on how powerful the visual was, although they did also question just how credible the scale was in terms of representing real data.


Icaro Doria. Meet the World, Brazil [Image] (2007, February 16). Retrieved July 28, 2016, from

4X4 Model for Knowledge Content

The 4×4 Model for Knowledge Content is a guide to getting people to engage with your website or online content brought about by the fact that many people will only spend 10 seconds on your website and even then most will only skim it. So your content needs a way to stand out.

The 4 models here were:

  1. The Water Cooler – Typically a headline. Content is succinct, direct and compelling. Its purpose is to grab your attention.
  2. The Cafe – Where the content is explored with more details. NOT a deep study. A progression from water cooler that explains the ideas not just introduce them.
  3. The Research Library – This is where you dig deep. Contains research and data to back up the water cooler and the cafe.
  4. The Lab – Users interact with the data from the research library. Rarest form of content but also the most powerful. Gives the users access to the data to interpret any way they like.

There are also four components involved here.

  1. Visualisation
  2. Story-Telling
  3. Interactivity
  4. Shareability


This following diagram was quickly created by me to better show this system. There was a visualisation similar to this was used in the video, but I modified it to better represent this method.


All information for this post was retrived from Bill, S. (2014). The 4X4 Model for Winning Knowledge Content. Vimeo. Retrieved 26th July 2016, from