The MoMA recently acquired the exhibition Dear Data, a joint collaboration between Stefanie Posavec and Giorgia Lupi. Stefanie describes herself as “an artist whose medium is data.” For 52 weeks, the two artists collected data on the intimate interactions of daily life. They initiated and sought to learn about each other via the medium of self-collected and self-reported data. Each artist would provide a visualization and a key, before shipping off little parcels of data across the Atlantic. The pair explored topics ranging from the number of times they looked at the clock, to the number of physical interactions, the number of apologies in a week, and the number of thank-yous — an entire friendship communicated through data.

Part of the beauty of the Dear Data project is its intentionality. Data acquisition on “human behaviour” is most often a byproduct — information collected passively to track where we spend our money, what ads we click, what we read online, what phone calls we make, emails we send, messages we read. And yet, there is an entire sphere where data has not yet encroached. There are (as of yet) no apps to track our indecision, the number of animals on a neighborhood stroll, our moments of impatience, or the number of times we laugh. Dear Data strives to capture the beauty of these daily rhythms through the unlikely medium of data.

Stefanie and Giorgia refer to the project as “Little data” in contrast to the omnipresent “big data.” The pervasiveness of datafication is inescapable. What we eat is tracked at the grocery store, school attendance and grades are stored online, even our spontaneous late night purchases of several years ago are likely whirring away on a corporate database.

And yet, the mistake of the big data revolution is the tendency to equate new data with new information, and a still further leap to imply that collecting data translates to meaning. We don’t learn new things about ourselves from the apps. We know what we buy, but human motivation remains obscured. Attendance records may be tallied, but databases miss the underlying reason such as illness or family dynamics. Furthermore, often the meaningful relationships in our lives are predicted by the absence of data. Facebook can tell when people are suddenly in a relationship, because the profile picture views drop to zero, the flirty comments are no more. The data encodes this as an abrupt phase transition: from the pixelated world into the territory of flesh and blood.

By paying attention to the little bits of information we don’t often collect information on, Stefanie and Giorgia challenge the status quo of data. Rather than collecting data purely as a byproduct of oft-commercialized endeavors, they exercise agency to collect the data for the story they want to tell from the get go. Cathy O’Neil, resident authority on data science, says that visualization is telling the story of “how the data came to be.” In contrast, Stefanie and Giorgia decide what story they want to tell—what aspect of their lives they want to pay particular attention to in a week—and then they tell it with data. In that sense, the project is deeply counter-cultural. So often, data collection is entirely passive, and the resulting data package is packaged and repackaged and sold around the internet to the highest bidder. It is sold in order to sell you things. Dear Data stands as an example of taking active control of the stories our data tells about us. It hopes to engage the full human and narrative potential of big data rather than taking an apocalyptic luddite stance.

The project sits in an uncomfortable space between communities of statisticians, graphic designers, and data scientists. Is the project art? Data? Does it matter? Work at the boundaries of disciplines like this often feels a bit homeless. Unlike data journalists and graphic designers, Stephanie doesn’t code much. Her data is collected by hand, typed into phones. Data visualization respects certain protocols for the most efficient types of visualization. Stefanie and Giorgia break those distinctions, bending axes, using color, size, shape in ways that challenge the viewers.

Much data visualization has a purely pragmatic angle. People look to charts when they want information about the effect on a bottom line, or when they want to represent numbers that have some sense of authority. Visualization aims to cultivate efficiency, whereas the artistry of Dear Data engenders awareness. Stefanie remarked that the year-long process of visualizing personal data heightened her attention to the topic of the week. On the week of cataloguing complaints, she sought to complain less, on the week of laughter, she would deliberately seek out occasions to laugh.

The project hypothesizes that counting may be a form of awareness. As a statistician, I live by a quote from Einstein, “Not everything that counts can be counted, and not everything that can be counted counts.” Dear Data reminds us that but when we stop to count the things that matter, when we truly pay attention, we can create beauty and meaning, whatever our medium.