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:



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