Every so often, we hear about people who are finding new, innovative ways to visualize data. In this version of Just for Fun, we sat down with Susanne Jaschko and Moritz Stefaner of Data Cuisine to talk about their brilliant, and sometimes tasty, take on making data easier to understand.
How did the idea of Data Cuisine come about?
SJ: In in 2011 I was curating a conference and workshop program for the Helsinki festival Pixelache. The program focused on mapping as a social practice and it also addressed the ownership of the data that we produce every day. From this the idea for the Data Cuisine workshop arose, since I felt that we are generally lacking an emotional attachment to data and that we should find new ways to look at data and deal with it. With Moritz, I found a renowned expert in the field of data visualization, who also likes to experiment and push the boundaries of his own discipline. Together we developed the workshop and have done it twice now.
MS: We were mainly just curious how we can connect these two worlds: the sensually rich, social experience of eating, and the abstract, cold world of numbers and statistics. In the workshops, we research ways to represent local open data in local food, through the inherent qualities of food such as color, form, texture, smell, taste, nutrition, origin, etc. The workshop is a collaborative research
experience, blurring the boundaries between teachers and participants, data and food. At its end, an local data menu is created and publicly tasted. We think we can learn a lot about food and data, by letting these two worlds clash.
Where do you get your data?
MS: Well, first of all, the data should relate to the place where the workshop happens—we like to “ground” the dishes by turning local data into local food. Second, the statistics we use should be striking, and relevant, but cannot be terribly complex. So, we investigate beforehand, which themes and datasets seem promising and interesting, but a lot is actually researched on the fly by our participants. It needs to come together in the moment—the right person, theme, and dish, and there is only so much you can prepare.
SJ: We propose to our participants to work with open data, since this is a rich field that still does not receive the public attention that it deserves. It’s surprising which kind of open data there is, once you start to dig.
What surprises have emerged from the data?
SJ: In Barcelona, some members of the Domestic Data Streamers collective participated in the workshop. They decided to collect data among their Facebook friends instead of using open data. They developed a questionnaire investigating the sexual activity of men and women, both single and in a relationship. The results of this data collection was relatively surprising, because it showed that women among their facebook friends who answered were by far more sexually active than the men, but that fewer women would have sex on the first date than men.
They visualised these outcomes in three dishes:
What other work do you hope to do with data? What’s next for Data Cuisine?
MS: We aim for a few more editions of the workshop, in order to understand the local differences better and continue to explore the medium. We might also vary the format in the future—one format we were considering is a high-end “data dinner,” which would put less emphasis on the collaborative workshop process, but more the final outcome and dining experience. And I would like to learn more about the science of cooking and the technological advances in the area—this field is buzzing right now!
What other ways could you imagine visualizing data?
SJ: I would like to continue trying to bring data into public space in the form of ‘social sculptures’ or installations that change over time and depending on the flow of data. What I like about this idea is that data is directly brought to the people who make that data through the way they
live and make their choices. Data as a processual public sculpture mirrors society, or a neighbourhood. This has been tried before: the D-Tower by Lars Spuybroek is an early example. Together with realities:united I worked on a proposal for such a data sculpture in 2012/13 for a square in Leipzig, a monument to freedom and unity. We made the second prize in the competition—so it won’t be realised. But its concept and aesthetics were provoking and opened up new direction in the discussion of what public monuments are today and what they can be in the future. Some of the key questions that we were exploring with the concept for the monument we formulated in a workshop concept.
Why do you believe data visualizations are important?
SJ: Most people don’t have an interest in statistical information, nor do they care about their own data. One of the starting points and motivations for Data Cuisine has been the disproportion between the amounts of data that each of us produces each day, our own data trails and our lack of interest in them. Another reason for Data Cuisine and an intense engagement with numeric information is that we usually get our information from the media, and by then it’s already edited or visualized and may be even twisted. We should start to look at the numbers ourselves, to use open data, to grow an awareness for our own data, protect and make use of it.
We think we can learn a lot about food and data, by letting these two worlds clash.
What was the most delicious visualization?
SJ: It’s very difficult to name single dishes, since they are all memorable. I would name the Tortilla Feliz Catalana from the Barcelona workshop and the Twisted Lasagne from the Helsinki workshop. The lasagne represents the ethnic mix in Finland with a spice gradient from 1990 on one side of the lasagne to 2011 on the other side of the lasagne. One could basically taste how immigration spiced up Finland. The tortilla was both visually intriguing and super tasty. It was inspired by the deconstructed cuisine by Ferran Adria, and is difficult and laborious to make. But the fine layers of pureed, baked, and cooled down vegetables were delicious and delivered a fine tongue experience.