This is the second part of a three part post on the work I have been doing over the summer towards my final postgraduate exhibition.
In the previous post I explained how I had built my own drawing machine, something that could take a digital input and make a physical analogue drawing from it. In this post I will explain why I decided to try and draw data.
I really liked how the mechanical mathematical way the machine interpreted an image and handled tone, especially when those images happened to be well known works of art:
Although fun, I knew this type of drawing was only a means to an end, I wanted to create drawings that tapped into the innate nature of digital media rather than copying existing images. A lot of the digital processes we use to make art in film, photography and illustration were developed in response to their analogue counterparts. To establish themselves they were framed as equivalent or superior to the analogue processes that proceeded them (I recommend Vilem Flusser’s ‘Towards a Philosophy of Photography‘ on this).
In a sense this framing of digital processes in relation to analogue ones shapes most of our interactions with digital technology, even today we still save ‘files’ into ‘folders’ on our ‘desktop’. Even the visual interface we use references processes and technology that are increasingly obsolete. In most cases we still use icon of a floppy disk to signify ‘save’, yet for anyone under 20 the action and icon it references will have no correlation. Cut and and paste is another good example, their digital uses are now far more common than the analogue processes it references.
I aimed to combine the serendipity of the drawn image with the accuracy and speed of digital technology when completing repetitive computational analysis of real time data. This would be an attempt to create physical representations of digital data.
i first became interested in data when making my polargraph, while the design and software is open-source and free I still needed to buy the hardware, the stepper motors, motor shield, counterweights etc. At the time some teaching I had agreed to do had fallen through so I was pretty broke, so I was completing online surveys in exchange for Amazon vouchers which I used to buy the components I needed. Not glamorous, or quick, but it got the job done.
Completing these surveys started changing how I viewed my personal data, my demographic data, age, gender, nationality became a commodity with economic value as did my opinions; whether I thought a certain brand was trustworthy, or ‘for people like me’. I also began to realise how much of this we give away for free to companies such as Google, Facebook and Apple I wanted to know if this data is so valuable to companies, allowing them to improve marketing strategies and increase profits could it be used for more positive ends? It while researching this that I came across the Open Data Institute and in particular their Data as Culture exhibition, see the catalogue below:
Data as Culture 2014 – Catalogue
I was really excited to see artists using data as medium, I especially liked YoHas’ Invisible Airs, a dada-like interpretation of Bristol City Councils’ expenditure database.
I decided that I would try and use twitter data as the raw material for the final drawings, it seemed like a good source of constantly changing information. I was also inspired my a number of other artists who had used Twitter in their data visualisation work.
In the final part of this post I get a bit techy and explain how I interpreted the twitter data in Processing and created drawings mapping the love and hate shared on Twitter in different cities around the world (below).
Drawing showing all of the Love and Hate shared on Twitter in New York – 31/8/15.
For more information about this project see my blog posts:
Draw bots and Data visualisation – Part 1
Drawbots and Data Visualisation – Part 2
Drawbots and Data Visualisation – Part 3