What does 1129 look Like?
My final project for my Master of Data Science and Innovation looked at hand crafting data visualisations. I have written a series of posts about my research and process which begins here.
One of the first goals I had when starting this project was to explore ways in which to explore visualization and empathy. The likes of Edward Tufte and Stephen Few believe that data visualisation is a rational, exacting science, that can be covered quite effectively by bar, slope and line charts. The bar chart though in a sales chart could easily be also used to illustrate the number of civilian deaths during WWII.
I admire the process that Giorgia Lupi shares in her post “Learning to See: Visual Inspirations and Data Visualization”. It outlines the process of using abstract art as an inspiration and foundation for a visualsation created at Accurat that illustrated Global Brain Drain. By using novel forms, Lupi and her team established a visual framework and language that pushes the notion that visualisation has fixed rules. It challenges the “efficiency” rule, as well as the the need to simplify and standardise.
This visualisation is engaging, it reveals patterns to ponder, it is playful and reminds me of a telegraph system of movement and connections — knowledge shifting between countries being carried by researchers. It brings an audience in and creates genuine pleasure and curiosity.
The Domestic Data Streamers, while utilising a very different delivery strategy, also aims to produce a connection with an audience. Based in Barcelona, they create large-scale data experiences that interact with people in a very physical way. They use installations, art work, sculpture, and video to help an audience come closer to a data set and help tell a data story.
Inspired by the scale of the Domestic Data Streamers work, I decided to work on large scale, hand made visualisation, again to show the number of deaths in the Rana Plaza building collapse. As mentioned in my previous post about the mourning shawl, I thought about mourning clothing, and the imagery of the shroud as ways to visualise death. I purchased a large piece of cream coloured fabric and where I created 1129 rows of stitching using a domestic sewing machine. The finished item is quite long, and when it is stored, it is rolled up like a scroll.
From a distance the piece of fabric looks frayed and with no embellishment. Close up though, it reveals it’s white on cream stitches, and that it is not the fabric that has frayed, but it is the hanging threads from the sewing.
There are 1129 rows of stitches. I captured the start and finish time every time I sat down to the machine to sew. When I started I had no idea how long it may take me. When I added it all up it was 13 hours. While at the sewing machine, I had a lot of time to think about the type of labour that garment workers do. Normally I only sew for a few hours at a time, and it is a pretty fun experience. I make a few things for myself to wear, but I am not used to long stretches. My body is not used not it, but nonetheless, the work is physically hard. At the end of a long stretch my back and shoulders would ache. I had to set myself regular breaks to get up and move around. This is not “easy” work. I also imagined what it would be like to work to a strict deadline, or be asked to keep working faster and harder, yet still maintaining the same quality. I was able to get up when I wanted to and stop when I wanted to. Some garment workers in Bangladesh work 12 hour shifts, seven days a week. When I planned on making this, it was more to show the scale of the people killed in the building collapse in a physical way. I did not imagine it would also show me a very tiny glimpse into what it’s like to sit and sew repetitively, over and over again. I am not claiming that in any way I experienced what a garment manufacturing worker in Bangladesh goes through in their working day, but the notes I scribbled down in between rows are things like “removal from the process / distance -> clothing, food, etc. We don’t know what others go through to create what we consume. How do we ever get to understand that process?” and later “We should try and ensure we understand the process with Data Science. The collection / the WHAT are we analysing …”.
I remember it being a really long and uncomfortable process, where I flipped from being bored and longing to do anything else, to being deeply moved as I focussed on what I was doing and what each row of stitches represented. When I finished, I stitched the two pieces of fabric together (I had to do two separate pieces as I would have never been able to sew it on my small machine) to make one long piece and rolled it out along the floor. I had experimented with using red thread before I started, but decided on white as a way of making the stitches almost hidden. The fabric looked beautiful with the white thread, and I was very moved by the sheer size of it, and what that size represented. I reflected on what each row stood for. It made me feel and understand the number of deaths in a way a number written down or printed on paper will never do.
Reaction
People are shocked when it’s rolled out. I have it in a scroll and when you roll it out, for a while it just keeps rolling and rolling. I encourage people to feel the texture that the stitches create, and if they move their hand horizontally along the length fabric, each time they feel a bump that represents a lost life. I look forward to sharing this with more people. Unlike the shawl, it’s not something I have with me every day so I don’t get a chance to talk to people about it as much.
I was pleased to complete a large project like this, as I’ve been wanting to play with visualising scale like this for a few years. I hope it’s a piece that I can share with more people and they also can reflect and understand what a large number 1129 really is, and maybe it will make them think a bit more about who makes their clothes.
Potentially I could gift this to CiC (if you are reading Theresa, the offer is there), so it can be hung in the office and new students can see that being a data scientist can be more than optimizing an algorithm, but also be about being an advocate or storyteller for data; what is the data and explain how it is being collected (or not). We can highlight injustices, or even pleasures. We can explain and translate in a way that makes people understand and hopefully change their point of view or at the very least see another point of view.
