Visualising data

As part of my course, I have taken on a data visualisation module. I wanted to understand the processes that go into visualising data because I wanted to adapt it to displaying results from a search made in a library catalogue. I thought that visualising results could make finding and understanding information a lot easier.

For example, I went to a talk where I was inspired by Todd Samuel Presner who talked about rehumanising data. He created a visualisation where those results that are usually hidden away at the end of a search – the not so popular results – can still be seen and even understood.

However, as I have been reading about how visualisation has been utilised within search results, I have found that it has been little used and have kind of failed. Thus I thought that taking this module would give me an idea of how I could utilise data visualisation in the future.

From taking this module I have begun to understand how much imagination and creativity goes into designing a visualisation. It’s not just taking a data set, putting in some code and creating some magic. You have to really think about your data set, what you want to visualise and how you want it to look.

This is a snapshot of the process I went through to extract data from a table and use code in Processing to create a visualistion. I identified the bits of information I wanted to extract from the table below (taken from the gicentre), and thought about how to extract the information from the table into Processing.


I also made sketches of how I wanted the visualisation to look. In this way, I could adapt the code to suit my design rather than accepting the original output as it appeared.

For example, my first output appeared as this:

It doesn’t look like any of my original sketches. But I could have accepted it, if I hadn’t really thought about what I wanted to visualise. I could have produced this kind of result using excel; but the whole point of using visualisation tools is to have something that says more about the data.

Thus, going through many trials and errors, I managed to produce my chosen design.


The visualisation has the value ‘100’ as a base point where the length of the rectangle shows the difference between ‘100’ and the value for each country. For example the rectangle on the far right represents 166 above 100; and the rectangle on the far left represents 53 below 100.

To be honest, I’m not certain that this is the best way to represent the data. I’m not sure that the data can be fully understood by someone other than me, but it looks pretty and I achieved what I set out to do.

In addition this isn’t the end. I want to experiment with colour and see whether the data can be enhanced in that way. But I have a long way to go.