Last week, I decided to track my music habits. Music is something that I listen to every day. It keeps me focused, lifts me up when I need a mood or energy boost, and often is selected based on what I’m doing.
Throughout the week as I was adding the data points, I kept coming back to the following in Chapter 2 of Big data in education: the digital future of learning, policy and practice:
From the eighteenth-century perspective, ‘data are apparently before the fact: they are the starting point for what we know, who we are, and how we communicate’, and were often perceived as transparent, self-evident, neutral and objective, ‘the fundamental stuff of truth itself’ (Gitelman and Jackson 2013: 2-3).Williamson 2017 (p. 29)
Music in the same way as data is described above is what I know, who I am, and how I communicate to myself. What I was not expecting, was that the visualisation of something that was meant to be ‘transparent’ or ‘objective’ would feel personal. When looking at the visualisation, I’m looking at what I needed, or how I felt at a certain point in time through the perspective of music.
In the uploaded image, I tracked on what device I listened on and the four playlists that were on rotation this week. I have Spotify on every device I own. I also decided to include a data point for any other time that I was wearing my headphones and not listing to music – when I sat in meetings.
In looking at this image and analyzing the week, I find that almost 50% of my days last week were filled up by meetings, and I wear my headphones more than I probably should… I also heavily rely on faster paced music to get me motivated for a workout, or when I needed to get something done. Weekends are, however, were filled with slower paced music when I was cooking brunch or cleaning up around the flat.
During working hours, I rely on my headphones. Alexa is rarely, if ever playing music as I work in the same room as my partner. At night, she is queen. My headphones and playlists are a way for me to transport myself to somewhere completely different when my partner is on a call (and I’m not).
As I couldn’t completely tear myself away from my list-focused and scheduled-oriented self, I decided to include a Y and Z-axis for the days of the week and rough waking hours to make it easier to read (as well as track). I knew that I would struggle to remember to jot down when I was listening to music, so I set an alarm on my phone three times a day to help me get into the habit. Maybe by the end of these next 9 weeks, data tracking will become a habit!
Looking through the Dear Data visualisations once more, I am so amazed at how creative Girogia and Stefanie are. It took me a while to come up with the symbols for meeting, phone, computer, and Alexa. I’m secretly hoping this exercise also sparks more creativity as I think through the data over the course.