I was really inspired by a couple of talks i had watched on ted.com, one by Misha Glenny
and the other from Loretta Napoleoni
. Both talks cover the different facets of the underworld which Micha Glenny refers to as the 'Shadow Economy'. I was so inspired by these talks that I decided I wanted to explore it further.Where is the data?
Limited to only free data resources online proved to be barrier since most of the data on the subject was only purchasable. In the end I was able to find a website called Havoscope
which provided data in a simple to interpret format.
How to visualise
I was particulary interested in the datanet and datascape representation styles of data. I was very impressed by the straight forwared delivery of information but also by the simplicity that could be achieved. having this in mind I worked on ways on how to represent my datasets which would allow me explore these visualiation styles. The process was hard and took a lot of brainstorming. Originally looking to take the datanet route I was puzzled about how I could show the relationships between countries on a world map. In the end, it came claer that the datasets did not support this kind of visualisation because the relations shown where not between locations but through value of the individual countries market and the products it possessed. Having given up this idea I looked further into a datascape theme but I quickly dismissed this idea given the amount of data I was trying present for each country.
Molding the data
The dataset from the shadow economy was very detailed and contained
different layers to express relations so decideding how to use the data
was very difficult. Besides the this difficulty it also allowed a lot
of freedom in terms of expressing the relations such as grouping by
greater region (i.e Asia), grouping markets by country or global
distribution or by the value of the market. To begin with I grouped the
data by individual country. After experimenting with this idea, i
quickly decided to group the shadow markets by global value. To me this
was a better choice because it was clearer to see the relations between
markets and value as well as patterns of global distribution. Visually,
this style of grouping aligned better with how I wanted to express the
data while still remaining visually appealing.
The final solution I chose followed a datanet style however I presented one side countries and on the other side markets and their values. The poster visaulise expresses the links between specific black markets and and shows its relation to countries which process them and to the value it contains in the country, region and globally.
With so much information being displayed, my key objective was to have a colourful, clean and informative poster that easy for people to look at it and learn something new from it. On side of the poster the user can see the countries and black market values and on the other side of the poster displayed is the different market activities and their percentage of the overall global value.