As part of a module at CIID we focused specifically on data visualisation as a means to learn the skills used for data gathering, analysis and distillation. We were challenged to find veritable, relevant data sets that we could use as a medium for not only building software skills but also to tell a story. A story that doesn’t need spreadsheet software or database management tools to access nor understand.

An concept that came early on was based on the notion of tracking the spread of an idea. What do I mean by this? We all know ideas are powerful. They spread from person to person through human communication. Acting on ideas like building, testing, analysing, investigating, destroying and rebuilding can lead to the development of new ideas. Simple yes? But how can you show this? How can you visualise this using data and tell the story of such a phenomenon?

So what I’m talking about here is essentially visualising two things:

1. The historical mapping of when an idea was introduced and, more importantly, which previous idea or development gave rise to this idea and when (which year).

2. The rate of diffusion of an idea/concept/product throughout the entire planet over time (years).

I mentioned above the spread of an idea was down to human communication. What better focus for deciding which idea I wanted to track the spread of? It became clear quite quickly that the one idea, the one technological development that has had the most impact in our time is the ability for humans to communicate over longer distances and over increased time spans.

So I chose the telephone.

This initial sketch shows my idea for visualising the two different sets of information. Each branch represents the “life” of a idea/product in the world. Depending on which idea it developed from or in conjunction with it would branch off from that line. The time axis on the bottom, inevitably, dictated where along the parent line the new line would break. The rate of diffusion was to be provided by the United Nations Commodity data for trade between nations, worldwide, throughout the late 20th Century (which ended up being my downfall but more on this later!). These can be seen by the bulging at particular points in the line. My key part of the visualisation was to communicate how some ideas or technologies become very popular and eventual drop off dueto lack of worldwide demand. Another interesting investigation was whether they effected each other. Did an increase in Colour Television trade spell any consequence for the trade of Domestic Radio’s?

I soon ran into difficulties when it came to just explaining the concept clearly. Upon reflection I feel that maybe I tried too hard to channel a core message, invariably upon every sketch making it more complicated!

To be clear, I didn’t start writing this post with a ‘success story’ in mind. This project would be in the Work section if the case was that it was over. No this post is about lessons. So without further a-due.

Upon reflection I realise I should really have made sure to secure the relevant data first before designing the visualisation. The UN operates an amazing data resource (COMTRADE) detailing worldwide commodity trade with each type of commodity classed by the Harmonized System. This system is used worldwide by traders, logistics and governments to make sure everything is classed in way that someone from Indonesia will understand someone from Brazil. But the problem is that the classification is updated every 4-6 years. This seems obvious since the commodities that were trading through out the world 30 years ago, even 5 years ago, are dramatically different in the present day. Unfortunately this logic made my life hell when trying to collect relevant data for my design idea. Trawling through hundreds of thousands of spreadsheets and combining data from different years between slightly different classifications was a very daunting task.

To give you an example. Anlog telephone sets were all the rage in 1992. Then they were simply classed as, you got it, Telephone sets. But the data becomes more complicated if we jump even just 15 years to 2007 when telephone sets are split between 3 classifications: General, Line and Misc. Compiling this data for the ranges that I needed would have taken me forever so I had to settle for a compromise:

That’s right. Only a range of 4 years using one classification, the HS 07 system. Obviously this was a major impediment to my original concept but if I had realised this BEFORE I developed the visualisation I would have done things differently.

But alas I continued. Besides the point wasn’t to create a world-changing visualisation, it was to learn.

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