For the past four days, I focused on my heart rate. This is something my fitness watch does for me, but usually, I don’t take much notice of it. However, from Sunday to Wednesday, I wrote down my average heart rate for each hour of the day.
My visualisation inspiration came from the ‘weather scarf’ ( Tweet by @porridgebrain (1344…497)). But instead of knitting, I decided to weave with wool, which I never did before. I allocated certain colours to the ranges of my heart rate, which you can see in the picture below.
It was so much fun because I not only learned a new technique (on a whole other level I processed my data, even more, this week) but I also got a feel for the ups and downs of my heart rate while the weave pattern came together.
It took me quite some time because I had to switch colours quite often. Nevertheless, I feel that through this approach, my data became even more visible.
You can spot four days: My average heart rate going down every night, whereas it increases throughout the day. I worked out twice (on Sunday and Monday), which is made visible by the pink thread in the pattern, representing the highest average heart rate these days. Of course, these data are not the most precise, since I decided on the average heart rate per hour and not the highest or lowest of an hour. Such a visualisation would look quite different. As I see it, it depends on what you set your focus on while collecting data, because the outcome can vary considerably!
What strikes me and worries me about tracking personal data with a device is how much of my information is online! The app on my phone is connected with the device: It offers me daily recommendations when it notices anything is off, for example, a shorter period of sleep or a higher heart rate than usual for a specific time of day. I sometimes receive the message that my heart rate at night was higher than usual and that an infection could be the reason for it, which was right when I contracted COVID! Anyway, ever since I notice how these kinds of messages trouble me sometimes. However, they shouldn’t, because often there is a simple explanation for my higher heart rate: being a coffee addict or more stress as a teacher in these times. But those information and background knowledge can’t be tracked by my device!
Wow, this is amazing!
Wow. ‘Woolly data’ is also a brilliant metaphor for what you articulate in your commentary. I especially liked this line: “it depends on what you set your focus on while collecting data, because the outcome can vary considerably”. The same could be said of how any analytics system is set up, but often as users we have very little sense of that! I wonder if making this woolly data visualization made you reflect on ‘learning’ at all? I say this in the context of work I’ve heard about that aims to use wearable heart monitors to capture learners’ states of ‘arousal’ during learning experiences. This is about collecting data about ‘proximal’ features of learning — and heart rate is said to be an indicator of students’ so-called ‘non-cognitive’ response to learning experiences by researchers working on ’emotional learning analytics’. Did anything in your week’s data collection of your heart rate indicate anything about learning?
This is astonishing! So creative.