This lecture extends upon the previous lecture and discusses historical examples. It also answers the question of the functionality of visualisation. Leon advocates that it is not just for aesthetic purposes but also because it allows us to gain an understanding and an insight into complex issues.

Leon utilises a book, ‘An introduction to information graphics and visualisation’ by Alberto Cairo as an example of the topic. Leon discusses the World’s population and discusses the fertility rate of women in each country whilst outlining statistics and the debatable explanations behind them. For example:

  • Rising fertility in poor regions is the reason why the earth has to support 7 billion people now with a forecast of 9 billion in two decades from now.
  • If the replacement rate in each country is below 2.1, the population will shrink overtime. If it is much higher than 2.1, there will be a much younger population further than the road, potentially causing issues, such as being more vulnerable to crime.

The author contradicts both reasons by analysing two trends. In wealthier countries, fertility averages are low however, it is beginning to rise. Poorer countries are steadily declining in fertility. In 1950, the average fertility per woman was six. As of 2010, it is below 2. The author suggests, fertility trends will potentially drop to 2.1 in the upcoming decades and the world population will stabilise and approximately 9 billion.

Visualising data and numbers allows the observer to save time and energy. The graph makes it easier to see the trends.

Leon also compares the fertility rates between Spain and Sweden and also displays a graph that compares international trends.

In this case, the graph highlighted some wealthier countries and some poorer countries and lists the reasons for the steady decline in fertility rates. For example:

  • An increase in per average capita income
  • Better access to education
  • Shrinking of infant mortality figures
  • Better family planning

In conclusion, readers should be given enough information to be able to follow an argument or use their own intelligence to come to their own interpretation and extract their own meaning.

As designers, Leon advocates that it is essential we honour intelligence and the curiosity of the data while developing it to be engaging and visually appealing.


The graphs that were displayed in the lecture were easy to follow as they were colour coded and allowed for the observer to establish an informative conclusion. I have been told in the past that the population of earth has exponentially increased and will keep rising. I like that Cairo shows evidence that this may not be the case and that earth’s population will stabilise at 9 billion in the next two decades. He shows graphs and evidence that clearly supports his opinion, as they are labelled and are created from reliable sources.

After watching four lectures, I feel I have gained a further understanding of data visualisation and its significance. I will try to apply Leon’s advice and honour the intelligence of data in my visual projects, while using my design abilities to engage the audience and illustrate valuable information in an interpretative way.


The functional art 



Brazil’s demographic opportunity 

References in APA

Brazil’s demographic opportunity [Image] (2017). Retrieved September 19, 2017,  i.pinimg.com/736x/63/7b/22/637b22f882f9ec5f39d013e1101948c1–information-design-adobe-illustrator.jpg

The functional art [Image] (2017). Retrieved September 19, 2017, from image.slidesharecdn.com/civilhackingshort-130601124311-phpapp01/95/alberto-cairo-visualizing-data-5-principles-to-live-by-2-638.jpg?cb=1370090973





Data visualization is both an art and a science. It can be simply defined as data that has been visualized. Data values are qualitative or quantitative variables belonging to a set of ideas. Data itself has no meaning. For data to carry on information, it must be interpreted.


Life Visualisation

Although infographics and data visualization are similar, they are not the same thing. The difference is that data visualization visually represents data, that allows for the audience to interpret the meaning accurately. Not all information visualizations are based on data, but all data visualizations are information visualizations. Data visualization aims to help people understand the significance of data. The beauty of data visualization is that patterns, trends and correlations can be exposed and recognized easier as opposed to just facts and theory.

Data visualisation is an essential part of the communication process. A data driven story without a chart is like a fashion story without a photo.

The growing scope of digital data has had a significant effect on our world, especially in the 21st century. Today, we are trying to understand the complex layers of the social, environmental and political systems. However, with new visualisation strategies, it makes it easier for us to make sense of it all. We are now a part of a data economy that is more complex and generative than what the world 50 years ago, could have possibly imagined.

“There is a tsunami of data that is crashing onto the beaches of the civilized world. This is a tidal wave of unrelated, growing data formed in bits and bytes, coming in an unorganized, uncontrolled, incoherent cacophony of foam. None of it is easily related, none of it comes with any organisation methodology.” –  Wurman, R. (1996). Information Architects. Graphis, 1997, p.15.

There are various ways for data to be visualized. Two examples include:

Line chart: Perfect for viewing data overtime
Bar chart: Perfect for comparing 2 variables


Line and bar chart

Thus, effective visualization helps users analyse and reason about data and evidence.


Before viewing this lecture, I didn’t know what the difference was between infographics and data visualization. Watching and studying the lecture gave me a clear understanding of the difference- that while not all information visualizations are based on data, but all data visualizations are information visualizations. Furthermore, the lecture also allowed me to gain an understanding of the importance of how data visualization can highlight patterns, trends and correlations that can possibly be missed with simply observing and analyzing theory.

I admire how Wurman uses the metaphor of a ‘tsunami’ that ‘crashes onto the beaches of the civilized world to describe the exponential rise of data in our technological world. I believe that data visualization can assist us to grasp some concept of the chaos of the world, so that we can gain a little understanding, to advance humanity and make the world a better place.

APA Referencing 

Life Visualisation [Image] (2013). Retrieved July 23, 2017, from https://www.google.com.au/search?q=data+visualisation&source=lnms&tbm=isch&sa=X&ved=0ahUKEwim2eTLs6fVAhVEUrwKHe2ICOYQ_AUICigB&biw=1920&bih=901#imgrc=EBbbkYry4RuhbM:

Line and bar chart [Image] (2015). Retrieved July 23, 2017, from https://www.google.com.au/search?biw=1920&bih=901&tbm=isch&sa=1&q=line+vs+bar+chart&oq=line+vs+bar+chart&gs_l=psy-ab.3..0i8i30k1l2.38513.40504.0.40615.….0…1.1.64.psy-ab..11.6.1278…0j0i5i30k1.6h8–v2lSho#imgrc=8IVYhkmpcniS0M: