Well, this was our last lecture, sad no? But it did leave me personally with a lot to think about. Data Visualisation should well be everywhere! and they are and I can't help but feel like shouting "Why wasn't I informed?!" cause you can do so much and connect information that well frankly might not be connected! Say for instance that Colea example people were getting sick they did a data visualisation and where able to deduce that it was a particular pump on a particular street corner that was the source of the trouble!
I thought that the idea of inbuilt visual wetware was a pretty good way of looking at it. Shapes, scale, colour, movement and position. These are the elements that effect the way we interpret information and were pretty good at it.
So by my immediate enthusiasm for dataviz I'm sure its becoming apparent what I intend to do! But the question is what kind of data am I going to be going to look at? My itunes library! and you must be like 'why would we wanna know about that?' but I'm going to track my music listening back as far as I can and then look for correlations between the music and my life and events that have influence what and how much I was listening to and if that's not good enough then I'm going to add in a friend's library for comparison and see how our listening habits and tastes have deviated from each other. Fun no? So I will be looking at play counts, date of import, date last listened and see if we can find any music experiencing the long tail effect and what is really just a fad.
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