Data Bakery

Sept 2019–Aug 2021

Data in the home are often perceived as passive, in the background, and are kept ‘just in case’ they are needed. With this project, we bring data to the forefront and create a ‘performative’ way of encountering one’s home data: by baking it into cookies. Data Bakery is a service that provides a cookie recipe based on two week’s worth of smart plug data in a home. The Data Bakery includes a printer, smart plugs, and recipe booklet/guide.

Data Bakery is one of the three artifacts in the Odd Intepreters family. View project details for Broadcast and Soft Fading.

Collaborators:

Audrey Desjardins
Jena McWhirter
Min Jung Koo
Philbert Widjaja
Nick Logler

The Data Bakery includes a printer, smart plugs, and a recipe booklet/guide.

The act of reading the recipe, deciding whether or not to measure precisely or alter the ingredients, and eating the cookies all offer novel ways to engage with data.

Each recipe will differ, reflecting how smart plug usage varies over time. The cookies become a materialized representation of months of living in a home with smart plugs.

Some combinations might be delicious, while others might be more questionable. Over time, as home dwellers collect various cookie recipes, and as they bake more cookie batches, they will start to understand how their data influences certain parts of the cookie.

In the accompanying booklet, a key is provided to explain how each of the 5 smart plugs’ data may influence the cookies.

One plug dictates the size of the dough balls, one controls how long the cookies will be baked—both changing the texture of the cookies, from thin and crispy to dense and cakey. Other plugs’ usage define what toppings will be used, from almonds to candy cane chunks; and another identifies what spice will be added to the mix: matcha, cinnamon, cayenne, etc.

Publications

Audrey Desjardins, Jena McWhirter, Justin Petelka, Chandler Simon, Yuna Shin, Ruby K. Peven, and Philbert Widjaja. (2023). On the Making of Alternative Data Encounters: The Odd Interpreters. CHI'23 New York, ACM Press.