Allowing Data to Just Exist
On the practice of self-tracking, documenting and archiving, and the need to interpret data
Due to my own consistent logging efforts, six months of my life now exist through charts. What started as a table that I drew on an A4 sheet with a felt-tip pen, has later become a growing printable template, with new columns added as time went on. And today it lives digitally on my computer, first as a spreadsheet then turned into code turned into visuals. I started logging data in hopes of sticking to a more regular sleep schedule, to get myself to make my bed in the morning—because that’s something I’m supposed to do, right?—and to keep track of a few other habits. I taped my monthly A4 tables next to my bedroom door to fill them out when I woke up and I did the same before going to bed. For the most part it became a morning and an evening task. And I started all this with no knowledge of the term “Quantified Self.” I wasn’t trying to quantify my being, to turn myself into numbers. But I also didn’t know what the term meant when it got brought up after I mentioned my tracking efforts to a friend.
The Quantified Self
The Quantified Self website (quantifiedself.com) states that “The Quantified Self is an international community of users and makers of self-tracking tools who share an interest in ‘self-knowledge through numbers.’” and Melanie Swan, in her 2013 paper on the topic describes the quantified self as “any individual engaged in the self-tracking of any kind of biological, physical, behavioural, or environmental information.” She also points out that health is often an important focus, although not always the only one. Oftentimes self-tracking serves as the way towards improvement and is done through various ways of logging the data. In recent years, wearable devices (such as smart watches and sports trackers) have become very accessible and there are various apps available (according to Deborah Lupton, there were over 160.000 of them on the market in 2016), which help with the task of logging and tracking, but they do not necessarily have to be used. Some log their data manually, for example on paper or in a spreadsheet.
“But I don’t do that"
Reading about the activity that I’ve been unknowingly engaging in for a few months, I felt some disconnect to what I read. I thought “But that’s not what I’ve been up to, at least not really.” Though I do use some tracking tools and and while it’s interesting to check how many steps I did in a day (and less fun to check how many hours I spent looking at my phone), at no point was I really after some well-defined, concrete end goal. I wasn’t painstakingly trying to improve my bed-making habits, not making my bed every single day had no consequence for me. But although it all began as an (at times futile) attempt at (self-)improvement, it turned into a routine, a ritual of sorts. I tracked just because it’s something I started doing and then I just kept doing it. In the evening it gave me a few moments to look back on my day. Maybe I noted down that I saw a cute dog on a walk I went to. What I didn’t know at the time, but it’s become clearer in retrospect, is that perhaps I used my tracking to document, rather than to analyse.
Garry Winogrand, an American street photographer, said
“I photograph to see what the world looks like in photographs.”Maybe I logged just to see what my months looked like in data.
Self-tracking efforts become a design project
In addressing my own experiences with self-tracking, the following questions, which became the basis of my research, came to mind: Can day-to-day self-quantification be used as a tool for reflection instead of improvement and optimisation, and how? Furthermore, how can the collected data be used for the purpose of archiving instead of analysing? And how can self-quantifying become a practice that isn’t rooted in the search for perfection?
So, what does life look like in data?
The question is a spin on the aforementioned Garry Winogrand quote. When taking pictures, all he seems to be interested is just that; taking pictures and then seeing the pictures he took. He stated that he wanted to photograph what he found interesting. Ian Bogost, in his video about Winogrand, says about this practice that “His works are not commentaries, they are precisely the opposite. Garry Winogrand makes photographs not to capture what he sees, but to see what he will have captured.” When discussing the subjects of the photographs, he notes that “they are there just because they were there. Because light bent through an aperture onto emulsion. Because Winogrand is a person and people sometimes find themselves at press conferences and zoos and rodeos. Just because.”
What happens if Winogrand’s approach to the subjects of his photographs is to be applied to how we look at data? Most times, and even by definition, data is the subject of analysis. In fact, the Merriam-Webster dictionary defines data as “facts or information used usually to calculate, analyze, or plan something.” It is something we draw conclusions from, something to be interpreted. But, if that is not what one chooses to do with data, is the data itself then rendered useless? Pointless, even?
Is it then, by definition, not really even data anymore?
Interpretation and drawing conclusions
In her critique of the quantified self titled “The dark side of self-tracking,” Alexia Boiteau identifies four points of interest when questioning whether the quest for self-improvement is worth it. In one of them she writes about how representing through data can lead to oversimplification which in turn could lead to a reductive picture of oneself or the world at large. “The body and the self become represented as an archive of identifiable, storable and processable data, numbers and values.” I wondered if presenting data points solely with pretty shapes and colours would also be a reductive strategy? When starting the project, I felt quite strongly about not being presented as a set of numbers, ones and zeros, but wouldn’t this then be just a slightly different version of it? I would now say that’s not the case. Because the intention of the end product is not to (primarily) and directly serve as a representation, but rather it is an end product that comes along with self-tracking activities. A result that doesn’t aim to push for any sort of determined outcome.
Again, in line with Winogrand’s work, there are no conclusions to necessarily be drawn from the images generated from my data collection. At least that is not their intent. There is no definitive conclusion, and the extent of their interpretation doesn’t stretch beyond defining and decoding what each individual element of the graphic represents. They are there just because. And if I only want to see what my day or month or the world around me looks like as a visual representation of data, do I want to make a conclusion after I’ve seen it?
Isn’t just simply seeing what it looks like enough?
Did I answer my initial questions?
Did I find answers to the questions about the possibilities of a reflective, archival, and non-analytical approach to the practice of self-tracking? I would like to think that some small, unique way, I did. However, new questions emerged along the way, as they often do.
From my own experience, I believe the overarching answer to the questions I asked right at the start lies in the practice of tracking itself. To make the action of logging a routine, a ritual in of itself. The data produced at the end of a period of self-tracking can exist as a result of the action and the effort to log it, but not for any further analysis or interpretation. It is then not seen as the end goal, but almost as a byproduct. And how said data is later presented also follows the same idea. If it is displayed in a more abstracted manner, the innate desire to find patterns or possible explanations within it can be deterred. However, doing so, by definition, defeats the purpose of data, which is for it to be analysed and interpreted. But I think that perhaps sometimes data should also be allowed to merely exist.
Conclusion, reflection and final thoughts
I understand that there is some irony in stating that data shouldn’t be interpreted. Especially since the interpretation of data is arguably the cornerstone of the data design practice. Of course I don’t think data shouldn’t be interpreted at all. It should be, that is after all its main purpose. But within my project, it made sense to question and explore the possibility of overlooking the core function of data in order to see what else it could offer.
When data is treated as both the material to design with and the content of a final outcome, it can be shaped in ways that tell stories and offer new insights, and that’s the power data designers hold. And I think these core principles should also be examined and looked at from a different angle from time to time.
Sources and references
Boiteau, Alexia. “The dark side of self-tracking.” Fabrique, 21 Feb. 2020, https://www.fabrique.nl/blog/ 2020/2/dark-side-self-tracking.
“Data.” Merriam-Webster.com Dictionary, Merriam-Webster, https://www.merriam-webster.com/ dictionary/data. Accessed 29 Nov. 2021.
Diamonstein, Barbaralee. “An Interview with Garry Winogrand (1981).” AMERICAN SUBURB X, 2008, https://americansuburbx.com/2008/10/theory-interview-with-garry-winogrand.html. Originally published in Visions and Images: American Photographers on Photography, Interviews with photographers, 1981.
Fraenkel Gallery. “Garry Winogrand.” Fraenkel Gallery, https://fraenkelgallery.com/artists/garry-winogrand. Accessed 29 Nov. 2020.
Lupton, Deborah. “Self-Tracking, Health and Medicine.” Health Sociology Review, vol. 26, no. 1, 2016, pp. 1–5, doi:10.1080/14461242.2016.1228149.
“Seeing Things - OOOIII.” Vimeo, uploaded by Ian Bogost, 15 Sept. 2011, vimeo.com/29092112.
Swan, Melanie. “The Quantified Self: Fundamental Disruption in Big Data Science and Biological Discovery.” Big Data, vol. 1, no. 2, 2013, pp. 85–99, https://www.liebertpub.com/doi/10.1089/big.2012.0002.
“What is Quantified Self?” Quantified Self, https://quantifiedself.com/about/what-is-quantified-self/. Accessed 14 Nov. 2021.