My Vectors in Last November
Zine Making with Small DataSpring 2024
@Workshop: Conversations with Machine, Carnegie Mellon University
Implementation tool: Excel, Indesign
Instructor: Audrey Desjardins
In this workshop, we explored physicalization of small
data under the guidance of Audre Desjardins. Participants
were instructed ahead to bring a dataset connected to
themselves. It could encompass any shape, materials,
document type. With limited time to prepare, I opted for
the most accessible dataset I could gather: my Google
Timeline.
Typically, I’m cautious about granting access to my daata to conglomerate, as I think it is unfavorable to become someone’s data sample without full awareness. However, since arriving in Pittsburgh last summer in 2023, I decided to permit Google to track my location. This decision was due to unfamiliarity with the neighborhood, and the potential benefits of retracing my steps when needed. Thus, my positions since August 2023 are well recorded and organized via its Timeline feature.
Looking into this data proved to be an intriguing experience. They let me extract the data in csv format, which details places visited, durations, states(e.g. walking or running) in chronological order. While others might perceive this dataset as mundane, because mainly I was at school or at home, it allowed me to glean insights into my daily routines and activities. I could discern how hectic my schedule was based on the variety of places visited. I thought I maintained a running routine at least three days a week, but it turned out that I adhered to this merely for three weeks.
Typically, I’m cautious about granting access to my daata to conglomerate, as I think it is unfavorable to become someone’s data sample without full awareness. However, since arriving in Pittsburgh last summer in 2023, I decided to permit Google to track my location. This decision was due to unfamiliarity with the neighborhood, and the potential benefits of retracing my steps when needed. Thus, my positions since August 2023 are well recorded and organized via its Timeline feature.
Looking into this data proved to be an intriguing experience. They let me extract the data in csv format, which details places visited, durations, states(e.g. walking or running) in chronological order. While others might perceive this dataset as mundane, because mainly I was at school or at home, it allowed me to glean insights into my daily routines and activities. I could discern how hectic my schedule was based on the variety of places visited. I thought I maintained a running routine at least three days a week, but it turned out that I adhered to this merely for three weeks.
Reflection
I had never thought data of individuals could be as meaningful as big data.
Through this workshop, I think no matter what size of data is, I can extract meaning from it upon closer examination. I particularly enjoyed the data editing process and I believe I should do it more often for my own benefit. When I open up data instead of keeping it hidden, I can discover its value. I see it as beneficial practice, especially for someone like me who struggles to explain things with patience; it is like a useful diary.