Why do we use graphs?

As data visualisation designers we use graphs to make comparisons easier. Therefore, selecting the correct graph is important. Today it is quite common for graphic designers to select the wrong type of graph for their data due to trend, aesthetics etc. Currently bubble charts are quite on trend, however using circles causes us to always underestimate the size difference. Something to consider when selecting a graph type is that our eyes are good at calculating one dimension, however we are not good at calculation surface area (height X weight). Squares are much easier to compare more accurately.

In Albert Cairo’s book, The Functional Art, provides a ranking of graphic approaches to data based on human perception.

Cairo, A. (2013). Why do we use graphs? [Image]. Retrieved 3 September, 2018, from https://vimeo.com/177306425

Something like shading on a map to show height is used as a general indicator. It doesn’t need to be exact it is simply for relative comparisons. However, comparing dollar values using a bar graph is more accurate as it allows instant comparison.

The 3 most common graph types are:

1. Time series chart
2. Bar chart
3. Scatter plot

Some examples of when to use certain charts:

Bar Chart: These graphs are familiar. They are one dimensional and easy to use to compare two things. They are best to use when comparing data across two categories.

Line Chart: This type of graph is used to display trends over time. For example the stock price over a 5 year period.

Pie Chart: This type of graph is used to compare relative proportions or percentages of information. For example the percentage of a budget that has been spent. A handy tip is if your data requires more than 6 pieces of pie, a different graph type would be more appropriate.

Most important aspect and why?

The most important aspect of this lecture was gaining an awareness of the importance of selecting the correct graph type to present your data. I have noticed the trend with bubble charts and have found them quite visually appealing, however hard to interpret. Therefore, it was interesting to hear that these are perhaps not the best graph type to use to present data to allow for accurate comparisons. The reason this was the most important aspect was because data visualisation is a new area of design for me, therefore I tend to think graphically rather than presenting the data in the best way to be understood. It is good to know that simple and familiar graph types, like the bar graph, are often the best form to present your data and that understanding the data is the most important aspect to remember. It was also interesting to learn that the human brain can only compare one dimension and calculating surface area is quite difficult. This is something I will need to keep in mind, again that understanding the data is priority over visual appearance.

Reference

Cmielewski, L. (2016). Data presentation styles: Why use graphs [Video File]. Retrieved from https://vimeo.com/177306425

Historical & Contemporary Visualization Methods: Part 1

Visualizations have been around for many years and are used to grasp complex data easily.
In 1812 Napoleon’s army invaded Russia, Charles Joseph Minard created an infographic to depict the magnitude of events. His infographic took a lot of data and displayed easily how things went from bad to worse for the army. This infographic is an example of how visualisations reduce the time needed to understand a given event. It gives the audience tools to analyse and make comparisons themselves.

Minard, C. (1869). Figurative Map of the successive losses in men of the French Army in the Russian campaign 1812-1813 [Image]. Retrieved 20th August 2018 from https://seanmunger.com/2015/09/28/napoleons-tragic-retreat-pictured-minards-famous-infographic/

In 1858, Florence Nightingale created the famous visualization about the deaths of British soliders in the Crimean War. Florence was a nurse who cared for the injured soldiers at the time. Florence noticed that many of the soldiers were dying unnecessarily and kept record of this. She published a monograph from her collected data which revealed that the real threat to British troops was not the Russians but disease. Florence’s graph revealed comparative data over time to give a holistic view of the problem.

Nightingale, F. (1859). Diagram of the cause of mortality in the army in the east [Image]. Retrieved August 20th 2018 from http://blog.visme.co/interesting-infographics/

Otto Neurath, a socialist and economist in Vienna, created a museum to make economics understandable to the uneducated. He created the International System of Typographic Picture Education. He created the concept within visualizations that rather than showing larger pictures to show more of something to show repetition of the same sized image. He believed in taking the information to the people rather than the other way around. He used the idea of using visual information to transform the masses. Below you can see his visualisation about Home & Factory Weaving in England. He communicates big ideas simply so that it is easy for the uneducated to grasp the information.

Neurath, O. (1939). Home and factory weaving in England [Image]. Retrieved August 20th 2018 from https://eagereyes.org/techniques/isotype

 

Most important aspect and why? 

The most important aspect I learnt from this lecture was the importance visualisations have in educating and revealing information that couldn’t be seen without them. For instance, Florence Nightingale’s monograph was instrumental in ensuring that the British army did not continue to die unnecessarily. Her carefully collected data revealed that the amount of deaths could be reduced, which would impact the British army positively. This historical data visualisation is important because it shows the power and impact carefully collecting data over a period of time can be. Florence chose carefully how to present the data in order that the information may be fully grasped. A bar graph could have worked for each aspect of the data, however it would not have depicted well the impact over time. Florence was aware of the story she was trying to tell and choose her method of visualization accordingly.

 

I found the information about Otto Neurath inspirational as he used his skills in design for a greater purpose. He used his knowledge of design to visualize important information that even the uneducated were able to understand. The reason I found this inspirational was because it was an important reminder to use my design for a good purpose not to just design for the sake of it.

Reference 

Cmielewski, L. (2016, July 25). Visualisation: Historical and contemporary visualisation methods- Part 1 [Video File]. Retrieved from https://vimeo.com/176255824

What is Data?

We live in a time where we all generate a lot of data. Everything we do seems to be connected to the online world and thus creates data trails. Every app you use, every site you engage with, every payment you make – it all generates data. Data is essential to helping us understand social, environmental and political systems. As the world changes and data increases, new visualisation strategies are needed to make sense of this data.

So what actually is data? Data is values of qualitative and quantitive variables belonging to a set of items and/or the result of measurements. (Waterson, 2016) Data by itself actually has no meaning. For data to contain information it must be interpreted to take on meaning. This is where data visualisation comes into things. What is data visualisation? Exactly as it sounds, data visualisation is the visualisation of data. It is one of the steps in data analysis and its goal is to communicate data clearly through graphs.

You have probably heard of the term infographic before. However, did you know there is a difference between infographic and data visualisation? Infographics are not necessarily based on data wheres all data visualisations are all information visualisations. Infographics often look pretty but don’t really contain a lot of information wheres data visualisations add meaning to information. For example the image below of an infographic about a process is not a data visualisation. It is a list of process not based on data.

Mcguire, S. (2018). Happiness tips infographic [Image]. Retrieved 10th August 2018 from https://venngage.com/blog/9-types-of-infographic-template/

Effective visualisation makes complex data more accessible, understandable and usable. It helps users analyse and give meaning to information.

As Data Visualisation Designers processing, analysing and communicating data creates many challenges. It is important to use the right visualisation type for the different types of data we need to visualise. The bar graph is the most basic and common visualisation, however it is the best when comparing two variables (see example below). When trying to decide what type of visualisation to use you should ask yourself “Why should I not do a bar graph?”

Unknown. (2015). Total revenue by product [Image]. Retrieved 10th August 2018 from https://irina150.wordpress.com/2015/10/08/bar-charts-versus-pie-charts/

The line chart or timeline (see example below) are the best default choice for looking at data over time. People are familiar and comfortable with both these types of visualisations and can read them easily. This is important as it allows for effective communication which is the foundation for our visualisation. The main role of the Data Visualisation Designer is to use data to tell a story.

Excel Easy. (n.d.). Line Chart [Image]. Retrieved 10th August 2018 from https://www.excel-easy.com/examples/line-chart.html

 

The 4×4 Model for Winning Knowledge Content 

Shander, B. (2014). The 4×4 model for winning knowledge content [Image]. Retrieved 2 August, 2018 from https://vimeo.com/100429442

 

Most important aspect and why? 

The most important aspect I took away from this lecture was that we as designers are to use data to tell a story. It is not about producing a “pretty picture” but whilst it is important to make visually pleasing, data visualisation is about interpreting data to give meaning and understanding. My understanding of data visualisation has already increased as I didn’t know that their was a different between infographics and data visualisations. My perspective has already changed on how I am to approach this semester and look to interpret data to tell a story. The reason this is important is because as communication designers if we are designing pieces that are not communication anything we have essentially failed at our job. Therefore, it is important to analyse data, interpret it and communicate it clearly so that the audience understands something that they wouldn’t have previously.

 

Reference

Waterson, S. (2016, July 18). What is data vis? [Video File]. Retrieved from https://vimeo.com/175177926