In this 4-week project, I finished two group projects and one individual task that is about data visualization. In the first part, I with my group collected, recorded and organized the data of “clothing” and presented them in a 3-D installation. The second part is about e-waste data visualization. in this part, my group presented the benefits of collecting phones over ten years in Australia and named “Old phoned = More trees”. In the last part, I found a new data-set about e-waste and made a 2-D data visualization poster of it.

20Figure 1. Personal data: Clothing (First version)
Figure 2. Final installation

4142Figure 3. E-Waste data visualization “Old phones = More trees”


Part 1: Personal Data

At the beginning, I was little confused with data because I had no sense about what data should we present and in what way. In the process of collecting, organizing and analysing our data, I understood we need to choose one data-set and make it have a story to tell and could communicate with viewers effectively. But the first version was not so successful. It was a little messy and there were some original data on the installation which have no meaning for communicating our data. After that we made a change of our data visualization. The second version is more simple and orderly that audiences can easily get the point “which colour is the most popular people wearing in winter”.

Part 2: E-Waste/Media Materiality

In this project, we also struggled with data at the beginning. We spent many times to find an interesting data-set. Finally, I found a data-set about collecting phones in Australia and we decided to visualize the benefits of collecting mobile phones over ten years in Australia. After doing the first part in this brief, I understand data visualization need to quickly and simply communicate complex information to a public audience unfamiliar with the topic. Besides, with following the theory of learning by doing, we made a model to test before we start installation. It really showed some problem which might be happened in the real installation. After discussed with my team members, we found a solution with our data visualization.


Figure 4. Details and process of “Clothing” data visualization



Figure 5. Model of e-waste installation




Figure 6. Details and process of e-waste data visualization


According to Tim Brown’s T-Shape Theory, “empathy allows people to imagine the problem from another perspective to stand in somebody else’s shows.” This really helps me in my group collaboration. Having reflected on this, I listened and considered my partner’s ideas when we were in discussion. And I gave my thoughts which build on their ideas after that. I think it is really helpful for a team work. For example, in these two group project, every step all was determined after discussion with my group. Although each of us think differently, but after much communication and discussion we successfully completed the project.

In this data visualization section, I tried to use design skills to present data in a visual way and make it beautiful at the beginning. I was wrong with data visualization. After this brief 2 project, I learnt that data visualization is not only to visually present data, but also through visualized data to help people understand and acquire information quickly and efficiently. So at the e-waste part, my partners and I tried our best to make data simple and clear for audiences to understand. We considered our data and choose corridor as our installation place which is aims to make data and audience have an interaction. In our installation, people can walk through it and be navigated by lines to reach each year’s data. I think this is really an interesting way to show our data to the audiences.


For this e-waste project, although I am very happy with our data visualization installation, but I received some feedback from audiences who think our data is a little hard to compare. I think maybe next time I need to do more test before I finish a project. And I will be focus on how to organize data and visualize them more clear and easy to understand in future. At the same time, I will avoid unnecessary elements and decoration in a data visualization project.

For the collaboration part, I understand the importance of communication. I learnt to be a listener and how to make an effective communication. According to Richard Sennett’s view, when you start with “It seems to me…” will be better to make an open communication than start “I think…” or “I believe…” to demand for a response in a discussion. I think it will be very helpful and useful in my future collaboration. I will try my best to be a good listener and a communicator.


IDEO CEO Tim Brown: T-Shaped Stars: The Backbone of IDEO’s Collaborative Culture [online] Available at: http://chiefexecutive.net/ideo-ceo-tim-brown-t-shaped-stars-the-backbone-of-ideoae™s-collaborative-culture/ [Accessed 4 March 2016]

Richard Sennett on “Together” [online] Available at: https://patrickhadfield.wordpress.com/2012/02/18/richard-sennett-on-together/ [Accessed 4 March 2016]

Manovich L (2010) What is Visualization? Available from: http://manovich.net/index.php/projects/what-is-visualization[Accessed 5 March 2016].



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