Map Critique: Dear Data
by Nelesi Rodriguez
Dear Data is “an analogue data-drawing project” –as the authors define it in its official website– created by Giorgia Lupi (Italian-born living in NYC) and Stefanie Posavec (US-born living in London), two designers who work with data visualization in their daily lives. Over the course of 45 weeks they simultaneously tracked (sometimes analogically, sometimes digitally) one aspect of their existence and created very beautiful and intricate hand-written visualizations of the data they collected. They also airmailed the weekly results of their explorations to each other in the form of postcards. The website dear-data.com documents part of the process and results of this experiment.
According to its authors, the goal of Dear Data was for them to get to know each other better while collaborating on a data visualization project, and to demonstrate “that you need to know almost nothing about data to start collecting and representing it” (we will bring up this last point later in the post_.
For the purpose of this critique, I’ve decided to review one week of postcards (week 6) — the one that documents seven days of physical contact in the lives of these designers. This decision allows me to anchor my comments about general features of the project in two images instead of being all over the place. Also, the topic of the postcards I chose relates more directly to the focus of my project for this class: the body as both a cartographic canvas and tool.
So, what’s on these postcards? The front of the postcards shows a drawing (usually abstract) that in reality is a hand-written data visualization. The back of the postcards contains the identification of the week and the topic being measured, instructions on how to decode the drawing, and mailing information. In this particular example – and this is something that also happened in other weeks – the authors also included some comments about their process of collecting or/and visualizing their data.
Though they agreed on the topic and established some guidelines for collecting, visualizing, and sending the data, week after week Giorgia’s “results” were substantially different from Stefanie’s. The differences might reside in the data collection system (which shows how different people can have different definitions of the same concept), in the data drawing (which speaks about the author’s style and even personality), or in traces of the postcards’ journey (which ultimately enriches the experiment if you consider the context and randomness as an actor).
When looking at these “maps of physical contact,” we should keep in mind that this project has an artistic focus: The authors had the explicit goal of a professional collaboration. Though the primary audience of these postcards consisted of Giorgia and Stefanie, the pair were deliberately attempting to create something that later on could be valued by the design community and the general public. However, I’m sure that this project helped them reflect on and better understand some things about themselves and each other. The list of the topics tracked during the 45 weeks, the design of each data collection system, the aesthetic and formal choices they made for the drawings, the traces of the postcards’ journeys: all these elements speak in some way about who these people are –and it is worth highlighting that the elements I just mentioned are not the data that they were supposed to collect, but all the things around it.
What interested me the most about Dear Data was the fact that the project is not so much about the data collection as it is about designing the instrument (and about drawing, in their case), and how those methodological-design choices speak about who you are. For my prototype, I thought I could use this idea to promote critical reflection around self-tracking practices. First, I identified an aspect of my life that I wanted to track: sleep. Then, I designed an “analogue measurement instrument” based on my ideas on what “sleeping well” means for me. Finally, I (informally) compared my instrument with some of the sleep-trackers available in the Apps Store. I hope we can consider designing the instrument as an exercise of mapping (I was “mapping my road to a great night of sleep”).
I chose to track my sleep because I think this is a part of my life that really affects the rest of my daily activities and because there are a considerable number of commercial sleep-trackers in the market. I must say I was not very sure about the topic because I considered it might be too superficial. However, it was interesting to see how designing my “measurement instrument” made me reflect about what are the elements I consider important in relation to sleep (for instance, I realized that I think that my partner’s presence-absence can affect my sleep quality).
In the process of creating and implementing this instrument, I also realized other things:
I felt the need to annotate almost every data entry I entered, which might mean that a) I’m not very good at operationalizing variables or b) sometimes it is difficult to reduce some information to data.
Creating data visualizations is hard. So even though Dear Data is supposed to demonstrate that you do not need to be a data specialist to practice self-tracking, the fact is that you need to put a lot of thought and dedication in order to make experiment work and look “ok.”
The available apps that track sleep look at very different variables than the ones I considered. I decided to use SleepTime for a couple of days to compare “the results.” In this case, the visualizations the app provided seemed limited, inaccessible, and irrelevant (what does exactly “deep sleep” mean, and how did they measure it?).
Designing the instrument was much a more reflective and insightful process than actually gathering the data. This thought made me think about an idea proposed by Dietmar Offenhuber last week about the indexicality of data. In his presentation, he said that indexicality was more related to framing than to mapping . Is it possible then to say that the instrument I designed is in a middle ground, a map that contains traces about myself and my cultural context?
 Offenhuber, Dietmar. “Sticky Data and Superstitious Patterns: Visualization Beyond Cognitivism.” AMT Data Visualization Lecture: Dietmar Offenhuber. The New School, New York. 3 Nov. 2015. Lecture.