Data Presentation styles consists of graphs to present information for the reader to easily interpret. Graphs come in many different forms and are designed for specific data sets and to convey the information the way it wants to be interpreted. Designers tend to use the wrong graphs to present data for the aesthetic purpose but fail to present the information to be interpreted the right way.
Example of a poor Data Presentation style – Bubble charts – Market Capitalisation of the worlds Biggest Banks
Bubble charts use area to show the fall in stock price from the year 2007 to the year 2009 where the area shows the decrease in the billions of dollars lost in stocks over the years. The reason why the graph fails to show accurate comparisons is because human brains are only good at comparing single dimensions like lengths. Our brains cannot compare complex things such as length and height to work out area. The circles make it harder to calculate the area when looking at it with the naked eye due to having the dimensions, also the shape of circles make it more challenging to work out the area as it requires the use of a formula to calculate it. Circles make the comparisons harder compared to squares as the flat sides allow for people to compare the size of the squares along other ones due to having simple dimensions and being able to line up the length and height with every square.
Example of a successful Data Presentation Style – Billion Dollar 0 Gram
The Graph consists of squares to compare the billions of dollars through the use of area between each square. Having the simple dimensions of length and height where each square can be stacked up against each other to compare size makes it easier for accurate comparisons.
How we use Graphs?
Different graphs are used to express information in different ways as some graphs show more accurate judgement and others show more generic judgements to make other information to stand out and be clearer. For example colour saturation and shading are used for more generic comparisons and are used on maps to show things such as elevation above and below sea level, heat, rainfall etc. Generic graphs usually consist of colour saturation and shading to provide vague comparisons of data. Graphs used for more accurate comparisons are positioned along a common scale for example bar charts and line charts where bar charts compare data in categories and line charts compare changes over time.
Commonly used charts
Line chart: Records values over a period of time recording the changes at each time increment.
Bar chart: Displays values of each category and allows for comparisons between the values in each category.
Scatterplot: Shows each variable as a single dot plotted across an X and Y axis.
Pie Chart: Displays the relative percentage of the information as a section of the chart.
It is important that designers consider the right visualisation approach for a specific data set as choosing a more aesthetic approach may result in the failure to convey the correct information in a data visualisation. Using simple visualisation methods are usually the most effective in conveying data effectively and having simple dimensions that can easily compare data all need to be considered.
Daniel Krivacic Data Visualisation 