The Data Cuisine Project Creates Infographics You Can Actually Eat

An experiment in data visualization puts unemployment levels in a sandwich, suicide rates in a cocktail, and sexual behavior in candy.

  • This dumpling dish answers the question: How often do couples have sex compared to singles? (All photos courtesy of Data Cuisine)
  • "Unemployed Pan con Tomate" This edible area chart shows the huge increase in youth unemployment in Spain.
  • "First Date Noodles" show what percent of men and women in Barcelona will have sex on the first date.
  • "Kippis!" This map of Finland shows the differences in alcohol consumption across Finland.
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  • "Tortilla Feliz Catalana" represents the state of well-being in Spain.
  • "Lakmoussetikka" This dessert represents the amount of berries picked in the very thin layer of blueberry on top, as compared to all the berries that could be picked, but are left in Finnish forest—represented in the amount of mousse on bottom.
  • "Happiness cocktail" represents not only the number of your Facebook friends, but especially how many of them are smiling on their profile pictures.

In the age of the listicle and the infographic, we’ve come to consume our information in a particular way. Our appetite for data is voracious, but we’re picky eaters: it’s got to be simple, visual, and shareable. Sites like Vox and Nate Silver’s FiveThirtyEight specialize in taking complex information and serving it up just the way we like it.

Susanne Jaschko and Moritz Stefaner’s Data Cuisine project takes a different approach. Over the course of two workshops in Barcelona and Helsinki, they’ve pioneered a literal form of data consumption: visualizations that you can actually eat or drink. Information is represented by the look, taste, smell, and ingredients of a dish; for example, pink and blue intertwined noodles representing the proportion of women and men who have sex on the first date (next to it, noodles lined up without touching show how many people abstain), or a lasagna whose spiciness increases in direct proportion to a country’s immigration levels over time.

These data visualizations are visceral, ephemeral and fleeting. You have to experience the information to understand it, and then it’s gone—or more accurately, it’s incorporated into both your mind and body.

We spoke to Jaschko and Stefaner to find out more about the project.

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How did Data Cuisine come about?
Jaschko: In in 2011 I was curating a conference and workshop program for the Helsinki festival Pixelache that focused on mapping as a social practice. 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 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.

What’s the purpose of the project?
Stefaner: We are 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. It is very unusual to produce food that “means something”. Usually, food is meant for enjoyment and to appease one’s hunger. Making food about something is a challenging creative exercise that forces us to think in fresh ways about food and cooking.

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What’s the benefit of presenting information in edible form?
Jaschko: Food is sensual and tangible, we can perceive it with all our senses and it creates an intense experience when consuming it. We have a personal and emotional relation to food: we very much like and dislike some foods, we associate certain people and moments in our life with a particular dish. Hence eating and cooking is a social and multi-perceptual experience, while data is often said to be abstract and dry, unemotional, non-tangible and non-sensual. By transferring data into the medium food, we can overcome those qualities of data, and take advantage of the qualities of food.

How do you choose the data?
Stefaner: 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 data sets seem promising and interesting, but a lot is actually researched on the fly by our participants. At the end, a local data menu is created and publicly tasted.

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How detailed and accurate can you be with numbers?
Stefaner: When it comes to precise quantities and differences, of course, our taste organs are more limited than our visual system. It is simply much harder to determine what is twice as sweet as opposed to a line that is twice as long. Then again, taste is a much more emotional and temporally complex experience than just looking at a dot on a screen. So, the mechanisms to encode information might be more fuzzy, but potentially much deeper. Here, precision of data readability is not of primary concern, but rather the overall personal experience and the dishes’ concept.

How much of the dish has to represent data?
Jaschko: There is no rule to this. We would like our participants to focus on the representation of data, but metaphorical additions in the form of garnish can be nice to add meaning and make the dish more expressive.

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Does each dish come with a written or verbal explanation?
Jaschko: The data dishes are not legible per se. Some look like ordinary dishes that reveal their meaning only by eating them. Others are more graphic and visual, but in general one has to be told what data they represent. We don’t think that this is a flaw of Data Cuisine, but that this way the dishes generate curiosity, which is the ideal starting point for a discussion about the story behind the dish.

Since only a few people can eat the dishes, isn’t this a severely limited way of presenting information?
Jaschko: That’s the whole point. Consuming a data dish means perceiving it with all your senses, and that’s a very personal experience. Data Cuisine is all about creating this personal, but nonetheless social experience.

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What are some of the most memorable dishes to come out of the workshops so far?
Jaschko: It’s very difficult to name single dishes, since they are all memorable and interesting. In terms of experience the Suicide Cocktail was one of the most memorable creations simply because it really tasted awful. Its recipe is based on the statistical data of both the relation of alcohol consumption and suicide rates in Finland. Creating a dish that tastes terrible is sometimes the best way to communicate a negative development or a problematic situation.

Are more workshops planned?
Stefaner: We aim for a few more editions of the workshop, in order to continue to explore the medium. We might also vary the format in the future: one format we are considering is a high-end “data dinner,” which would put less emphasis on the collaborative workshop process, but more on the final result and dining experience. We would like to include new approaches and technological advances since this field is truly inspirational.

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