LECTURE POD 3- Historical and contemporary visualization methods (part 1)


Data visualization example (1): Data visualization strategies have been utilized over two centuries. Lecture pod 3 first discusses a data visualization that depicts the failure of Napoleon’s invasion into Moscow which occurred in 1812.


Napolean invasion chart 

A French engineer created this map, 50 years after the failure of Napoleon’s invasion into Moscow which occurred in 1812. This diagram displays several different variables.

The thickness of the line indicates the strength of the army at critical points. From left to right is the army crossing the river, with 422,000 and arriving in Moscow with only 100,000 men. From right to left (the darker line) shows the army returning to the west. Only 10,000 men survived. The vertical lines connect the temperature to the location.

Data visualization example (2): The second data visualization that lecture pod 3 discusses is one that was created by Florence Nightingale who played a significant role in the Crimean War (1858). The Crimean war was between the Russians and alliance with the ottoman empire and the British. Florence nightingale also helped to care for wounded soldiers.

The graph demonstrates that soldiers died from diseases more than wounds in battle. It goes around in a circus for a full year then crosses to the second year (left to right).

Nightingale wasn’t just famous for being a nurse, she was also the first female statistician. She was a significant part in developing proper sanitation for wounded soldiers and helped solve malnutrition among them. The graph below demonstrates how the death toll of  soldiers decreased over a period of time due to Nightingale’s effective attempt to prevent disease and malnutrition by providing proper sanitation and adequate nutrition.

Although her charts were not be perfect but they were a huge innovation in her time.




Nightingale visualisation 

Data visualization example (3): The third example that lecture pod 3 discusses is the work of Otto Neurath (1882 – 1945). He was a pioneer for socialism. He started a museum where he aimed to make social and economic relationships understandable, especially for the uneducated.

He developed a system known as the ‘international system for infographic picture information.’

Neurath also introduced exhibition packs that were made for the general people, as Otto believed that museums should be brought to the people, not the other way around. These were shipped all over the country and put on display at all sorts of venues to widen ideas. The precedent below displays a photograph of Neurath cutting out pieces to create an exhibition pack to distribute to the masses.


Neurath photograph 


Viewing lecture pod 3 has allowed me to gain an appreciation of how one of the most significant strengths of data visualization is that it can reduce the time to understand a certain event. Attempting to analyse paragraphs of texts, facts, theory and trying to make sense of it can be quite tedious and I have found that data visualization has augmented my capacity to absorb the data efficiently.

Another aspect of this lecture that I found intriguing was how Neurath created educational visualizations that could be communicated effectively towards the masses, including the uneducated. As education was a luxury during early 1900’s, I admire that Neurath acknowledged this and put in considerable effort to ensure his message reached the masses through an easy-to-understand method.

Lecture pod 3 has allowed to me to gain an understanding of the ways that data visualization was historically used and how effective it has helped us interpret data in a unique way that allows us to identify trends, patterns and correlations to advance our understanding of the world.

References in APA

Napoleon invasion chart [Image] (2016). Retrieved July 26, 2017, from http://www.google.com.au/search?q=napoleon+data+visualization&source=lnms&tbm=isch&sa=X&ved=0ahUKEwiyyPr7oKfVAhUKwbwKHWAqBmMQ_AUICigB&biw=1920&bih=950#imgrc=FCt4y-Pl4KRuoM:

Neurath photograph [Image] (2010). Retrieved July 26, 2017, from www.google.com.au/search?biw=1920&bih=950&tbm=isch&sa=1&q=otto+neurath+exhibition+pack&oq=otto+neurath+exhibition+pack&gs_l=psy-ab.3…33209.36271.0.36448.….0…1.1.64.psy-ab..11.1.204…0i8i30k1.MTRBnzSYurw#imgrc=ubUz6q-qNxAT5M:

Nightingale visualisation  [Image] (2017). Retrieved July 26, 2017, from https://www.google.com.au/search?biw=1920&bih=950&tbm=isch&sa=1&q=florence+nightingale+data+visualization&oq=florence+night&gs_l=psy-ab.3.1.0j0i67k1l2j0.704123.705668.0.707212.….0…1.1.64.psy-ab..12.2.677.e8dvL4r_S6U#imgrc=9s6FSEpRZ7JfZM:






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: