The beautify of data visualization | David McCandless
How we can find ourselves in data | Giorgia Lupi
The Future of Data Visualization | Jeffrey Heer
Visualizing ourselves ... with crowd-sourced data | Aaron Koblin
Above all things, Lupi’s notebook for tracking herself caught my eyes. Once, I had written a diary about my smartphone usage log. I had to write down for what, why and how much time I had used it, as Lupi did. Even before the half of day was gone, I could find out how often my smartphone’s notifications interrupted me and made me turn on the screen.
A few months ago, a new feature called ‘screen time’ has been added to iPhone, which shows what type of applications I have used for a day. But soon after I used this feature, I turned it off. It was really meaningless data for me that how many hours I spent on social networks, YouTube or etc. What I wanted to know was a context that I didn’t know, just as I could get new insights about myself, writing the smartphone log. All the screen time told me was just a number, no more, no less.
As Lupi found herself in data, and also as I did, I couldn’t agree more with what we need is an effort to discover 'human’ from data.
Why visualization of data matters?
McCandless quoted Hans Rosling’s saying, “Let the dataset change your mindset.” And he stressed the importance of the power of it, that it can also change your behavior. Wrapping up, he mentioned information problems in our society from the overload and the saturation to the breakdown of trust and reliability and runaway skepticism and lack of transparency, or oven just interestingness. And he suggested a solution, which is ‘visualizing information’.
By visualizing data, we can explore with our eyes a sort of information map. we start to see a different relationship, patterns, and connections between numbers. In Lupi’s word, it’s like a lens or filter to discover and reveal ourselves, human nature, stories and eventually humanities.
Data Humanism – ‘Dear Data’
The project 'Dear Data’ by Giorgia Lupi has been often mentioned in our last classes. In the TED video, her notebook for ‘Dear Data’ was shown up in the corner of the picture, of which checking time and tracking its context. Finally, we could see first-hand how she observed herself, collected her personal data and processed it. She manually drew on a postcard-size sheet of paper, which is completely analogue. Time checking, for example, the vertical axis meant 24 hours and the horizontal axis meant the days of the week. She used 10 kinds of symbols, which tells the contexts of checking time. Likewise, through the process of actively noticing and counting actions of herself, she became much more in tune with herself and aware of her behaviors and her surroundings. The core value she wanted to tell us with this project could be summed up in 'Data Humanism’, which means that data should be truly meaningful and representative of human nature.
Aaron Koblin collected his data using so-called 'crowdsourcing’ technique through Amazon’s Mechanical Turk(MTurk). MTurk is a crowdsourcing marketplace, in which a requestor outsources the very simple tasks to crowds with a very small pay. The task is something that human can do much more effectively than computers. The data collected through MTurk is different from the traditionally collected data in that it is a work of labor created individually for the entire project. The data of other visualization projects were collected from something that exists already somewhere in the world. The data are given a specific meaning only when large amounts of data are collected and presented with a single big picture. However, the data collected from Koblin’s project was systemically planned in the first place, and the stories of workers who created each data are alive. With a micro view, as well as a macro view, people can discover social and artistic meanings from the data.