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Final Project Proposal –Data Sculpture

Collaborator: Henry Haoyu Wang
Date: Nov.6, 2019


During the first meeting, we decided to make a physical data sculpture which both she and I had the same interested in data and how to make data more meaningful. We brainstormed last week to discuss possible topics we were both interested in. Finally we narrowed our topic range to 4 problem:

  • How technology especially social network/ machine learning change our environment, or change the human behavior.
  • What’s the relationship between happiness and money?
  • How can we visualized and managing our stress?
  • What’s the relationship between law and ethics?

Feedback From the Class

All these ideas are sad, or people don’t want to hear. How can we encourage audience play and enjoy this experience?  

Think about both and data set and the interaction.

Think about a specific interaction for this data set, interaction should make sense for the data set.

Those feedbacks were really useful, so we began to rethink our topics.

Research and Inspirations

We started look at art/design projects deal with data and technology. 

This is the project we get most inspired about. Think about data process in an eco-system. And use user interaction to influence the data/interaction process.

With these projects, we have the design goal is that have user interact with the sculpture, and after the interaction, the user will have a better understanding of the data process.

We are both interested in data and we went in deep to talk about how our privacy data was used and made profit and the rights and balance between data trading and usage. We found that we were both relatively ill-informed in terms of this topic. So we decided to dig more on this topic.

Research Digging

I did lots of literature review, trying to understand what kinds of data was collected from ours and what was traded in the data market and how this made profit (especially advertising).

Data Supply Side: Media companies, service provider.

Companies that collected data can be divided to two parts: (1) online data provider: (Facebook, Twitter, Uber, … etc); (2) offline data provider: Free wifi service provider, shared bike and other real service that can collect offline data.

For those companies which claimed to protect users’ privacy like google, apple etc, they collected all kinds of users data and stored them in the remote server. They won’t leak our age, gender etc to other companies. But they still traded our behavior data (e.g. what information you browsed and when and how long) as cookies to the data exchange platform.

Middle Side:

Data analyzing companies, like consulting companies (Accenture, BCG … ), bought data from supply side and make conclusions and products.

Demand Side Platfrom (DSP)

DSP collected cookie data from users across the devices and media and created profiles for each cookie ID. Once the Ad exchange market released positions for ad, DSP targeted user profile through cookie mapping and bought the ad positions across the platform and media for suitable companies that need advertising.

The truth is, the behavior data drew a relatively complete profile for each of us, although they didn’t know the name, which influenced our behaviors in the real world.


Final Topic

Although there is a increasing awareness about big data and data privacy, most people don’t really know what parts of the data is used or sold to the company and how companies make profit from them. Therefore, we think it’s meaningful to unravel the mystery of data flow from users to companies and advertising sides.

We will use cookie as the metaphor for the internet “cookie”, data is the power and money for the whole flow. 

Plan Next Week


  • These Friday coming up with three sketches/project detail plans that could work for rapid play-testing. 
  • Shopping over this weekend, get materials we need for next week.
  • Start make next Monday, come to next class with three rapid prototyping.  
Research side
  • Keep researching on digital data privacy…
  • The business model behind the social network process.     
  • How would the interaction we designed make sense to the user?

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