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How 2 Data Pros Became Friends by Exchanging Data Visualizations of Their Lives on Postcards


Data can be seen as an abstraction at best, or at worst, a way to introduce the robotic quality of programmatics into creativity. We might associate it with digital's way of converting the tangible, the soul of things, into pixels—compressed files that can be more easily stored and tracked, but that also, in the case of art like music or films, siphon away some of the original's quality (while dulling our appreciation of it). 

It probably doesn't help that, to advertisers and marketers, we are also data—people reduced to demographics, custom profiles, brand affinities and buying preferences that must be pushed toward optimized touchpoints. 

We concede that all of that is pretty gross. But is it the whole story? With data, it never is.

Over the course of a year, two data professionals who were overseas acquaintances embarked on a neat experiment called "Dear Data." Giorgia Lupi, design director at Accurat, and Stefanie Posavec, an independent data illustrator, got to know one another by sending each other weekly postcards of data visualizations they created. 

The topics ranged from the mundane, like how often they checked the time, to things like how often they heard a curse word. 

"'Dear Data' was conceived as a new type of correspondence through creating and sending hand-drawn data postcards across the ocean to each other," says Posavec in the video below.

Lupi adds: "By counting and reducing to data the most shameful or personal revelations"—like the number of curse words they heard over a week—"they somehow felt not so shameful anymore. They are data." 

The project has since been converted into a book, Dear Data, with a foreword by Maria Popova of BrainPickings.org. The original postcard collection has also been acquired by MoMA.

Check the video out below. It's followed by an interview we conducted, some neat photos of the postcards (courtesy of their U.S. publisher, Princeton Architectural Press), and a presentation they did at Visualized. 

Click on any image to make it larger.

AdFreak: Tell us where you both are from, and what you were doing.
Stefanie Posavec: I am originally from Denver but have lived in London for the past 13 years. I'm a designer, speaker and teacher for whom data is my favored material and subject. In my day job, I create projects ranging from data visualization and information design to commissioned data art. ... Also, in 2013, I was Facebook's first data-artist-in-residence at their Menlo Park campus. 

Giorgia Lupi: I am an Italian information designer living in New York. Originally trained as an architect, I then studied design at Milan Politecnico, where I obtained a PhD in information design. I am co-founder and design director at Accurat, an award-winning data visualization design firm based in Milan and New York. 

Giorgia's visualization of the number of times she checked the time, and its key:

What inspired this project, and how did you find each other?

Posavec and Lupi: We only met in person twice when we decided to embark on this project together. We were both speaking at the Eyeo conference in the summer of 2014, and a plan to collaborate was hatched, as they usually are, over a few beers! 

We both have a very analog approach to working with data, which is relatively unique in our field, so we thought it would be interesting to work together to create a data project that showcased our interest in the analog, using a slow, manual method of rendering data. 

We also took the biggest constraint as a design one: One of us lives in London and the other in New York. How can we exchange our data drawings? 

The idea of becoming "data penpals" and sending postcards to each other across the sea seemed very compelling, so "Dear Data" became our way of getting to know each other.

Stefanie's take on time-checking:

Each week, from Sept. 1, 2014, and for a year, we collected and measured a particular type of data about our lives. We used this data to make a drawing on a postcard-sized sheet of paper, then dropped the postcard in an English "postbox" (Stefanie) or an American "mailbox" (Giorgia)! Eventually, the postcard arrived at the other person's address with all the scuff marks of its journey over the ocean—a type of "slow data" transmission. 

Also, we were also curious to see if it was possible to get to know a person only through the medium of data and drawings. 

Giorgia's complaints as a sheet of music: 

After some experimentation, at the very beginning we decided that we wanted to try to gather data that a computer or app on our phone couldn't gather, so we focused on a very human way of gathering data, as opposed to relying on technology to gather it for us.

Also, from the beginning we wanted to focus on the analog, as the very act of drawing our data helped us extend ourselves as designers. By removing technology from the equation, we've each been forced to invent 52 different visual languages, as hand-drawing with data leads to designs that are incredibly customized to the data one is counting and working with. 

A common approach in data visualization design is to visualize data using tools that often return a very standard visualization, but by hand-drawing our data, we were compelled to craft visual models specifically for the dataset we were dealing with. At the same time, by radically limiting ourselves and our tools, we could "spend time" with our data and were able to understand it on a deeper level.

Stefanie's complaints, which resemble a sea anemone:

How did you read each other's data?

Once we got the delivery in our mailbox, we would spend time with the postcard, deciphering what the other person encoded, and how to unfold the narrative of her week through her drawing. But we most often texted each other to comment on tiny details, or even ask for more. We like to say that data should be seen more as a beginning of a conversation rather than an ultimate answer to any questions. 

What did you learn from each other and this project?
We both learned to be much more aware of ourselves, our behaviors and our surroundings. It was a long-term self-investigative project that touched several topics at the same time. Some weeks were particularly insightful, especially ones that touched particular "buttons," such as our obsessions—or ones that were more personal, such as the relationships with our boyfriends/husbands, for example. The major insight we both had is to learn how to practice paying attention.

Times (and reasons) Giorgia checked her phone in a week:

How was conveying information this way different from using words, pictures or video?

We believe data collected from life can be a snapshot of the world in the same way that a picture can capture a moment in time. Data can describe the hidden patterns found in every aspect of our lives, from our digital existence to the natural world around us. 

Once you realize that data can be gathered from every single being and thing on the planet, and you know how how to find these invisible numbers, you begin to see these numbers everywhere, in everything. We hope that by highlighting the ubiquitous, almost domestic nature of data, our work will be a relatable way for a wider audience to learn about it. 

We hope this will function as a "stepping stone" for interest and engagement in some of the bigger issues surrounding data, such as big data and data privacy, in society today.

As designers, we've not only observed our lives as data for one year; we drew it, we found visual shapes for it. And visualizing our logs helped us "see" the patterns hidden in our data in a much more impactful way. 

What do you think data says about us? How has it changed your perspective of data and its possibilities?
This project definitely was an intentional attempt to show data is not scary and not necessarily "big," but is ever present in everyone's lives. We are all made of small and big data, quantitative and qualitative. It allowed us to talk about data with an audience that is not only made of designers or data geeks. We explored how data can help us understand personal experiences and people's lives. 

Data is often considered to be very impersonal, but this project aims to highlight the opposite through the exploration of using something seemingly "cold" to communicate messy, emotional aspects of being human. 

Stefanie's phone addiction:

Will you continue sharing data this way as friends, or do you plan to expand the project to others?

Well, after a year of postcards, and a book, we are planning new ways of collaborating, but still always with data. 

And as for expanding the project to others: Since the project was made public, we have seen hundreds of postcards made by people who, after hearing our story, wanted to try the process for themselves. Many are seeking out their own data "penpals" and setting their own yearly challenges to draw data. 

We are also touched at how many young children are reading their parents' "Dear Data" book and are excitedly drawing their own data! 

More incredibly, teachers from grade school to university and beyond are using the "Dear Data" format to teach students the world of data—an amazing and humbling result from what started as a side project. 

We are most interested in exploring projects that harness this collective action as we move forward. 

What's the big learning you want to share with people, brands or data companies?
We are said to be living in the age of "big data," where algorithms and computation are seen as new keys to universal questions, and where myriad applications can detect, aggregate and visualize data to help us become these efficient superhumans. 

"Dear Data" approaches data in a slower, more analog way. It is a "personal documentary" rather than a quantified-self project, which is a subtle but important distinction. Instead of using data just to become more efficient, we argue we can use data to become more humane, and to connect with ourselves and others at a deeper level. 

Over a year, we shared everything about ourselves in the form of tiny quantitative bits, addressing and then revealing the most hidden patterns of our inner selves. 

Many people associate the "quantifiable" and "quantitative" with precision and objectiveness, and they are drawn to personal tracking by the idea that this will solve some of their problems, and maybe find rational answers. We think those kind of investigations aren't really about finding definitive answers about ourselves; they are more about raising novel questions. 

We didn't do this for optimizing our lives. We have always been more curious to discover even little things, and the process of discovery and experimentation are intrinsically motivating and personally rewarding. It has been like being our own personal anthropologists. 

Below, find the keynote Lupi and Posavec conducted for Visualized. Their website also includes information (scroll down) on how you can find a data penpal, teach "Dear Data" to students, or share learnings with the creators.

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