Street Event Mapping SF, Data visualization


Since 1769, San Francisco has been one of the most significant cities in the United State of America. During the Gold Rush period, it was the attractor for many people who were in the pursuit of new economic wealth. In addition the city of San Francisco had a significant role during the World War II. Now, as a global city, San Francisco generates new types of effects on the qualities of our economic and living conditions by supporting global companies such Information technology enterprise, such as Google, Twitter, Facebook and so on. Apart from its historical significance, nowadays, San Francisco stands as an important touristic attractor. Thus, San Francisco can be considered as a single active living organism that functions as an aggregation of people’s individual intelligence. Intelligence is addressed as an accumulation of experiences regarding places (secret spots), preferences (historical place to buy Ukulele in SF), interests etc. In this context, my interest lies in revealing the “third place” as a space that encourages people to share their individual intelligence and perception of the city. In order to reveal the third place, I consider the understanding of homeless people’s life important, since it differs substantially from the life of an average person. Homeless people utilize urban environment at the same time as their house, their workplace, their sleeping place etc.

During my research on the homeless population in San Francisco, I recognized different types of homeless people, based on their way of living. Among those different types, I wish to focus on those who tend to form a daily routine, for instance, the ones that have developed particular skills based on their interest (musical instruments, crafting etc.), or the ones that belong to certain groups etc. I consider these groups not as deprived groups, but as memory of the city, because they have developed methods to take advantage of the urban environment in an intelligent way that is not easy to perceive otherwise. The before mentioned, motivates me to reveal and visualize space as a third place, as the place between home and workspace, where people can relax and share their interests.




During my research, data can be considered as a tool for visualizing the patterns of similarity and difference network based on people’s interest. Data makes it possible both to perceive and understand the third data that control different perspectives in an indirect way. I believe that visualization, as an instrument for communicating ideas,
can shift our way of thinking and behaving. For example, if the energy consumption of a house could be visualized as disproportionate to its size, people would be able to perceive their energy consumption based on the size of their houses. If their house shrinks, this means that the consumption of energy is too high. Iin the same context, visualization of trash tracing or sharing a taxi in NYC done by “SENSEable City Lab” can be considered as examples for raising people’s awareness. Data visualization can be considered as a positive motivation for people to rethink their living condition and urban environment and not as something that urges people to shift their way of thinking entirely.

What if we visualize the human experience regarding urban condition in a tangible way? What if such individual small intelligence can be transformed into a swarm of ggregated intelligence in the urban context? Although there are tons of places where people can state and communicate their opinions and ideas in the virtual world, in reality, people tend to disregard the potentiality of space to operate as a collective platform of sharing interests, by repeating the same routine between home and workspace. So, what if I am able to reveal a space in the city, where people can participate in as a third place, that can also be considered as a gateway between the real and the virtual world? Termite taxonomies provide a good example for addressing collective intelligence. Termites’ individual intelligence is insignificant, but when populated, they construct 30-meter-diameter mounds. I wish to learn how to reveal possible third place’s pattern and how to generate collaborative urban intelligence, based on data visualization as the main research tool.

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