Tag Archives: opensource

Twitter Data Drawings – VIDEO

I’ve put together a quick time-lapse video to show some of the process behind producing the twitter data drawings I exhibited during my final MA show.

I shows the machine in action so should hopefully help people understand how the marks were made when looking at the final products.

The video features 3 pieces from the exhibition. The first is a drawing of all the ‘love’ shared in Wales on the 9/9/15. The second comprises of 4 larger drawings showing all of the ‘love’ and ‘hate’ shared in New York City on 4 consecutive days leading up to and following the anniversary of 9/11. The final piece shows the ‘love’ and ‘hate’ shared in 4 different cities around the world on the 9/9/15. The cities (clockwise from top left) are: Singapore, London, San Francisco and Paris.

For more information on the process behind this series you can read my other blog posts on the project:

Draw bots and Data Visualisation (part 1 of 3)

or see more images in my portfolio.


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Drawbots and Data Visualisation – Part 3

This is the final part of a three part post on the work I have been doing over the summer towards my final postgraduate exhibition. In the previous posts I explained how I built my drawing machine and why I decided to try my hand at some data visualisation. In this post I will explain a bit about my process in collating and visualising the data to make drawings the illustrate the amount of love and hate shared over 24 hours on twitter in different cities around the world.

Essentially I will try to explain how I got from this:

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to this:

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to this:


If you haven’t already guess this post my get a bit techy, but I’ll try keep it brief and punctuated with lots of pictures.

So it started to dawn on me that I was going to have to do some coding for this project, of which my sum experience to date was a bit of HTML and copying and pasting Arduino sketches. So I began to tentatively look for a platform/language that relatively quick to learn with good online documentation and, as a broke student, ideally something free and open source.

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Processing fits the bill perfectly, it’s an open source platform based on Java designed for artists and designers. I won’t go into it in too much detail here, but I’ll definitely do a post of my favourite art projects built with it at some point. Tou can check out loads on the Exhibition section of their website.

One of the Processing’s biggest advantages is the huge online community using the programme, as an open source programme users are constantly contributing, by sharing projects and offering support through forums and building new libraries.

Once I had decided that I would use twitter as my data source I needed a way to interact with it’s API, after reading Jer Throp’s great tutorial on this, I decided to us the Twitter4J library.


Inspired by Twistori (above) I began playing around making programmes  that searched twitter for different terms on twitter and displaying the tweets on screen. seeing all this data pop up was a pretty spooky experience, of course it was all made public by the users and could be found ‘by hand’, but seeing it pulled from the internet by an autonomous programme got me thinking again about how much info we are happy to put out there. It also made me realise how banal most of the stuff people on twitter talk about, and just how much people love One Direction (it’s a LOT):

WARNING: as you can probably guess, tracking all the hate on Twitter is not a particularly life affirming past time and some of the language in this video is pretty unpleasant. Don’t blame me, blame society. You have been warned…

However I was finding that the same tweets were coming up again and again and if I wanted to create something that could keep track of the times a term was used over a set period I would have to utilise Twitter streaming api. This proved slightly more complicated especially when filtering very popular terms such as ‘love’. The word was being used so often globally that the programme couldn’t keep up. This meant I was getting very similar values each time (the maximum number of requests the programme could handle in the time frame), you can see it in the images below (love is shown to a different scale to the others otherwise the whole box would be black):

To bring the numbers down to a more manageable level I implemented a location filter, which used longitude and latitude to put a bounding box over an area. The twitter API then sent all geotagged tweets from within that area. As I couldn’t combine a key word and a location filter I had to then make the programme break each tweet down and ‘read’ it for the key words.

This gave me the raw data I needed, a long list of how many times ‘love’ and ‘hate’ were mentioned on twitter on different cities around the world over a day. I was feeling pretty smug, but the only problem was that on its’ own, the data looked pretty uninspiring:

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I experimented with representing the data in a number of different ways:


‘Love’, ‘hate’ and ‘envy’ shared on twitter in San Francisco over 24 hours

These were just visual aids for my benefit, it was the polargraph that would need to interpret and draw the data:

Looking at the way the pendulum-like way polargraph drew, I (with help from my dad) developed the programme so that it would plot the data diagonally following the line of the pen, rather than simply from left to right top to bottom (see below). I was hoping this would make the images easier to ‘read’ but it also opened up interesting possibilities for displaying the finished drawings.

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I decided to present the drawings in grids of four, the drawing below shows four consecutive days in New York:


and this one shows the same day in 4 different cities (clockwise from top right; Paris, London, San Francisco and New York):


I felt presenting them in sets allowed for an easy way to compare the images without being too prescriptive. Individually these images are difficult to interpret, when presented together they given one another meaning providing a frame of reference that allows interpretation to be a creative rather than scientific process. Time flows from the centre of the grid out, like ripples in a pond. There is both an individuality on commonality to each location/day that I find intriguing. I like how visual pieces of information they provoke questions and challenge preconceptions. what are the concentrated areas of love in Paris? Why does San Francisco, a city with a historical reputation for free love, have such a proportionally high concentration of hate?

Of course, the whole notion of measuring our emotions digitally and distilling them into a drawing is a little tongue in cheek, but it does raise some interesting questions about the limits between computer and human interaction, especially in the nuanced ways we utilise language. The programme does not have a sarcasm filter for example. It did get me thinking about how extraordinarily complex language is, it’s a wonder we understand each other at all.

I will be showing a number of drawings and the polargraph in action in my final postgraduate show at Aberystwyth University School of Art:



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

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Drawbots and Data Visualisation – Part 2

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.

IMG_3997I 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

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Draw bots and Data visualisation – Part 1

Over the summer I have been working towards my final postgraduate exhibition, as it opens next week I thought it was a good time to (attempt) to write up what I’ve been up to.

Since first working getting to grips with the open source prototyping platform Arduino in 2013, when making an interactive audio screenprint. I’ve been interested in combining emerging open source technology with tradtional artistic media.


In Gas 2013 (above) technology was applied to an image created by hand to make it interactive, I became interested to see how this technology could be incorporated into the making of the image itself. It was about this time that I became interested in the open-source and maker movements, I liked to democratic, collaborative values at their core. I also saw their ‘hacking’ and repurposing as a subversive yet positive way of combatting the incredible wasteful nature of the cycle of upgrading and disposing we seem to be locked into with modern technology. A product of structured obsolesce and our closed-source system I increasingly see the rate of technological progress as being set by market forces as opposed to actual technological discovery. (I recommend Maciej Cegłowski’s piece on the future of the web on the nature of technological progress).

I decided I wanted to make a machine that could ‘draw’ in the physical sense, it would create a physical, analogue image based on digital data that I gave it. About 30 seconds of googling showed me I wasn’t the only one, and there was already an online community of people making and sharing images created by their ‘drawbots‘. After studying a number of Instructables I made a number of prototypes, which seemed as good excuse as any to raid me and my brothers boyhood lego stash. As you can see the initial attempts were pretty crude and could only really mange basic shapes and patterns.

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The next design I decided to try was a hanging pen type plot called Polargraph, after seeing Sandy Noble’s excellent instrucable, seriously, check it out. Based on a draw bot called Hektor (2002) byJürg Lehni & Uli Franke
2002 (below), a polargraph consists of a pen suspended between 2 stepper motors run from an Arduino and motorshield.

Despite its rather basic appearance it’s an incredibly versatile drawing machine, not least thanks to the open-source controller designed by Sandy in Processing (a java based programming language designed for artists and designers, more about that in part 2). Once I had it up and running I started putting it through its paces:

Once I had got the hang of it I decided to see how it coped with some some iconic works of art:

To test how it handled drawing vectors I combined it with a programme I had been working on in Processing and turned it into a photo booth:
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I was really excited with the results, I loved how it combined the serendipity of the physical drawing materials with the precision and repetition of their mechanical means of production. Things like tone and quality of line take on a different significance when they are products of mechanical reproduction. It made me question the emotive value we attribute these qualities.

I knew I wanted to explore the relationship between the emotive power of a drawing and its mechanical means of production further. I decided I would try to create physical analogue drawings of digital data. To do this I would need to learn a heck of a lot more about coding and data visualisation, something I will explore in part 2.

Here’s a video of my polar-graph in action:

This is the first part of a 3 part post on this project, read the other posts here:

Drawbots and Data Visualisation – Part 2

Drawbots and Data Visualisation – Part 3

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Gas – interactive Screen Print

The seed of this piece work was planted at the international printmaking conference Impact in Dundee 2013. After presenting a paper on my work I attended a demonstration on ‘conductive ink’. I had no idea what conductive ink was but was curious to learn more. The demonstration was my first introduction to Bare Conductive a water soluble ink that conducts electricity. In the demo we drew circuits to light a LED:

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Here he is, by connecting a battery between his glasses and smile you complete the circuit and the LED on his nose lights up. It was fun, but what really got me interested was the potential to use the ink as a sensor, by running it through an Arduino.

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now a capacitive sensor the drawing can sense how close or far you are from it and brighten and dim the LED accordingly.

I knew I wanted to produce some work based around this, but the ideas stayed on the shelf until I was asked to take part in a group exhibition. The venue was Aberystwyth’s Oriel Nwy, an old Harley Davidson show room it is a large open space with great big windows and great views from the street. I decided this would make it a good venue to show an interactive print installation based around what I had been doing with Bare Conductive ink.

I wanted to turn the idea of a gallery as a sterile environment in which one may look but at all costs not touch on its head by creating a multi-sensory piece that actively encourages physical interaction.

Gas was the result, a collaboration between myself and another artist showing in the exhibition Kim James-Williams, I felt her beautifully balanced pen and ink drawings would echo the aesthetic of the wires and circuits behind the scenes. The image we chose was a drawing of the gallery itself, I love it, the composition makes the gallery seem impossible light almost like it is about to float off, fitting for something called the ‘Gas’ Gallery.


I screen printed the image in Bare Conductive ink and attached it to an Arduino, the Arduino would then take the capacitive reading from the ink and create a varying audio output, the idea was for it to sound like a theremin (not sure what one is? Listen to the Star Trek theme tune or The Beach Boys ‘Good Vibrations’, or for a more contemporary example:

I was really happy with the end result, it was great to see people interacting with it at the opening, nervous at first, they became increasingly bold and confident and ended up ‘playing’ some really nice stuff.

Here are some photos of the opening and a video of the finished work in action:

My film piece ‘Flicker’ was also included in the show. I was really thrilled to be asked to take part in Transitions at Oriel Nwy with such a talented group of artists, you can see there work in the Catalogue. We were really grateful that John Harvey agreed to open the exhibition, he gave a really encouraging and inspiring speech at the opening, which you can read on his blog.

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