Investigating Data Collected from P’s Exercise Habits
P is a very keen runner, having taken part in a two marathons. As such, P told me that he usually runs 2-3 times a week, and that usually he tracks his running abilities using his phone. We agreed that together for this week of data tracking, P would pass over his running data for me to use and analyse.
We also agreed that P would not use his running data with the phone data (steps, distance etc) (see here) as it would then become hard to distinguish between the data sets.
Complications arose around anonymising the data gathered, as we did not want to reveal the route P ran as it began at his door step. The data initially gathered plotted his route on a map.
Together, we plotted our own map using technological tools to represent the data gathered. Further, P also felt it was unnecessary to quantify the runs he completed in my project – I agreed with this sentiment especially as he was adamant about this statement. The map presented below is a product of our conversation about how we should display the data gathered from his running activities during the week.
The diamond at the top of the map indicates P’s home and starting point – observing the map, P usually take a clockwise route. P retracing of his route on a second run is indicated by a thicker line.
I spoke to P about how he felt during his runs this week. He completed two runs on Tuesday and Sunday. He said he ran considerably longer on Sunday, as he took the full route he intended. Whilst on Tuesday he reached a point and turned back (seen at the bottom of the map). I asked him why this week he only ran twice as opposed to his usual three, he told me he just didn’t find time this week between work and socialising. I asked what he thought about the visualisations we had made of his running paths. He said he like how abstract it was, as it was easy to understand yet showed no specifics. Only he could understand where all the points on the map where in the real world setting it took place.