Week 5: Non-Visual Data Representation

This week our assignment was to make a representation of a public dataset that is experienced with a sense other than sight.

I had previously experimented with weaving data (thanks to Ashley Jane Lewis who taught me how) and made a woven version of Tauba Auerbach’s alphabet using the binary system:

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I also lived in Peru for a year and was influenced by Incan history and especially the quipu - a record keeping device that uses string and knot systems.

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I knew I wanted to expand on this work. I have been working on the subject of rain gardens and flooding recently. I have also been using 311 (partially related to the flood work) and have been thinking about local data and situated knowledge.

I have also been inspired by Nathalie Meibach’s woven sculptures. 

I liked the small side by side aspect of the alphabet pieces as well and started thinking how smaller bits could be stitched together.

I started to think about ways to differentiate woven textures

  • tighter/looser

  • warmer/colder

  • smooth/rough

  • yarn/mixed materials (beads?)

Then I started asking myself, what kind of data would I want to feel? Or what could be important to encode?

I was thinking about the discussion we had around Lon/Lat in class and it made me wonder what it would be like to weave the previous visualization I made of flooding events. I had helped with a dinner project with Marina Zurkow where she made tablecloths out of three portions of the NYC map - what would a woven tablecloth look like? Could I do one for each borough? What would they look like woven together? In my first semester at ITP I created a data visualization sculpture called Data Structures which was a data representation similar to this idea made with projections and cubes. Recently I’ve been thinking about Shannon Mattern’s article Post-it Note City in which she advocates for mapping evictions. I like the idea of weaving a visualization of evictions and leaving a hole instead of doing a stitch where people have been evicted - if it were a blanket you would feel the cold in those spots.

She asks: “Beware the prioritization of flashy maps over the quality of data they present or the value of insights they generate.” What kind of insights would or could this blanket generate?

“I asked Baykurt, Riano, Canteli de Castro, and other designers to identify ways communities can use maps to assert agency and disrupt the neoliberal, algorithmic forces shaping the built environment. One theme that came up repeatedly: visualizing data on housing evictions and gentrification.”

In thinking about weaving approaches, I have also been inspired by my friend Rachel Snack who weaves landscapes and then photographs them in the landscapes. 

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What does a landscape woven out of data look and feel like? Could you “wear” a map of NYC?

I initially imagined being able to map this on the individual level, but I found an online tool that maps evictions in NYC and realize there are way too many evictions to be able to do this on an individual level. The tool also has evictions by zip code and community district. Even by zip code, New York may have too many to weave (over 200) They have the past 3 years, so I could make three weavings. I decided to start with one year (2018).

I began by translating the map into a weaving pattern. Then I started weaving this into my mini loom. I was working with yarn that I already had and immediately wished I had a bigger variation in texture and size, which would accentuate the holes more. I think that it may need to be more granular than the representation I chose of one stitch per zip code in order to have a more clear effect.

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The result isn’t how I had hoped, although you can see some holes in the pattern. I have the colors going from dark to light signifying housing disappearing, but the aren’t close enough for this to be apparent and it’s also too hard to tell a difference from feeling their textures. At first I didn’t like how messy it looked, but then I started to like this accidental aspect because that’s often how data is. It’s not large enough that you can really feel the heat or cold while holding it, but in a future iteration I can imagine how this could be successfully presented.

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