Once I had finished turning the mixture back into powder form, I started planning how much powder I would use for each pollutant at each site. Below the image shows my working out.
I was now ready to set up my black backdrop for the video. Kasia agreed to help me with the recording and distribution of the coloured powder. I booked a camera from the Kit room at LCC and positioned it to begin recording.
I first started with Elephant & Castle data. In the middle of the backdrop is an object that relates to the place. In this case, I collected some rocks, dirt and a cigarette butt that I found near the monitoring sensors. We then began to throw the powder above the objects. The recording below shows how we did this.
The video below shows the footage taken whilst the powder was dropped over the objects.
Now that I had finished one location, I had to clean up the area to get ready for the next location. This took quite a long time as the powder became stiff when exposed to water. When I had wet the backdrop, it actually looked better than when it was dry. I did get some nice process photos I would later use in the magazine design which I was really happy about.
Below I have attached all the video outcomes for each site.
Euston Road. Objects: Fizzy strawberry straws plastic wrapper, mars bar wrapper and gravy pot lid found along Euston Road.
Old Street. Objects: Plastic bottle and nitrous oxide (laughing gas) canister found near Old Street roundabout.
Westminster. Object: Metro newspaper found on the ground.
Here are the data visualisation photos for all sites: (From left to right: E&C, Euston, Old Street, Westminster)
Here is a spread view of the magazine I designed.
On the left page you see an abstract visualisation of where each powder landed, and how much of it there was out of 100%. Below that there is some information on the objects in the centre and a map showing the location. On the right is the data visualisation photo result. I am really pleased with the magazine. I had never done design in this way so I was really excited to. I think my design looks good and consistent, and my colour scheme matches the data visualisations.
Feedback
Today I presented my project to the class. Some of the main points brought up:
"Instead of distributing a magazine, maybe you could include the main spread of your data visualisation in newspapers. That way they would have more reach, especially if the data visualisations focused on a bigger area, like a borough."
This is a very good point and would be a fantastic next step for my project, especially if the data I use is is broader. For a whole month or year instead of just one day.
"You could have focused more on the interactive aspect of the powder. The images are static so you could have taken it a step further"
"It would have been great to see you throwing the powder on someone to see the effect."
The two points above link together. It would be great to do something more with the powder, maybe throw it on someone and see how they would react. What if pollution was actually visible like powder? I have over-exaggerated the looks in order to provoke a more significant reaction from the public. Maybe this reaction isn't noticeable with the magazine outcome I have chosen. And maybe it would be if I throw powder on somebody.
"I like that you've included QR codes on each photo"
I have done this because you cannot show video in a physical magazine. This way, if anyone is interested in my process, they can view the videos on Vimeo.
"The visualisations look very beautiful"
Overall, I was really happy with my outcome. I am glad that I chose to visualise my data physically as it's a different and something I have never done before. We tend to focus on digital outcomes in IID, but the physical is also important as it can have a deeper effect on a user. The photo outcomes do look beautiful considering they were shot outdoors in bright daylight with only a black backdrop. My next steps for this project would be to focus on a broader set of data as that will create a deeper effect than just showing one random days data.
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