I discovered Data Cuisine a few weeks ago and was immediately intrigued. As described in their tagline—exploring food as a form of data expression—the project combines two of my favourite things: eating delicious meals and talking about information visualization.
The basic premise is simple: people attend a workshop where they use local data (demographic, economic and others) to create meals that not only visually represent the data, but also use the data to dictate ingredient amounts, cooking temperatures and other such variables. Then, of course, they enjoy their data-inspired meals.
To learn more about this data visualization project out of Europe, I reached out to Susanne Jaschko and Moritz Stefaner, the people behind Data Cuisine, to have a chat about what they do, why they do it, and why they chose food as a way to teach people about data. Here’s an excerpt of our conversation:
It’s easy to get distracted by the mouth-watering photos on your website. Other than tantalizing meals, what exactly is Data Cuisine, and how did it come to be?
Suzanne Jaschko: Back 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 we produce every day. The idea for the Data Cuisine workshop arose from this, since I felt that we generally lack an emotional attachment to data and that we should find new ways to look at data and deal with it. With Moritz [Stefaner], 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, hopefully with more to come.
You mentioned that we need to find new ways to look at data with a closer emotional attachment—what made you decide to use food as that lens for data exploration?
SJ: Food is very social: we sit around the table, eat and communicate with each other. Food is also sensual and tangible; we can perceive it with all our senses and it creates an intense experience when we consume it. We have a personal and emotional relation to food: we very much like and dislike some food, 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 of food, by representing it with dishes, we can overcome those qualities of data and take advantage of the nature of food.
Our senses of taste are very subjective, and using food as a form of data visualization carries some serious issues because of the way we all perceive taste differently. How do you take that into account in the work you do?
Moritz Stefaner: I’ve mentioned this before, but it’s worth repeating: generally, when it comes to tasting 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 twice-as-long line in a graphic. 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.
Depending on the theme, a case could also be made for dishes that don’t taste that good. One example of that is the visualization we made of noise pollution with salt.
In the end, our goal is to create eating experiences that teach you something about the data; taste is one dimension you can vary, but there is also temperature, texture, amounts, the plating and all the cultural connotations different dishes and ingredients have. All of this plays together in creating a successful dish. Precision of data readability is not of primary concern, but rather, the overall personal experience, and the dish’s concept.
You’ve been very vocal about using emotional connections through media like food to teach people about data. Why do you think it is important for people to understand how to read, process, use and visualize data?
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 even be twisted. We should start to look at the numbers ourselves—to use open data—to grow an awareness of our own data and to protect and make use of it.
You’ve held two of these workshops so far, and you have more planned. What do you hope people end up learning after a workshop? What new things are they able to do?
SJ: We hope that the participants have a better idea of the city or country they are living in. The workshops are based on local data, so we actually learn a lot about the places, their specificity and problems. Of course, participants also learn some new cooking techniques or food combinations, and they acquire a basic knowledge of data visualization and representation. On this basis they can continue to experiment with Data Cuisine and use it as a tool to communicate or stimulate discussion.
Sounds like a fun, informative and delicious project! Do you have any appetite (no pun intended) for bringing the Data Cuisine workshops across the ocean to North America?
MS: Yes, that would be great! We have a few contacts and prospects, but nothing concrete lined up yet. If you know of anyone who can help, let us know; it would be great to do a workshop in various parts of Canada and the United States, with lots of relevant local issues and a rich mix of culinary influences.
All photos courtesy of Susanne Jaschko and Moritz Stefaner. For more information or to reach them, please visit Data Cuisine’s website.