Once I encountered the data set of Robin Weis , I knew I wanted to create a physical data representation of crying data. Specifically, my idea was to create a data physicalisation: a physical artefact that represent data through it material and geometric properties . Data physicalisations have been created for centuries (see dataphys.org/list), however, no known example represents crying data.
Initially, I wanted to use Weis’ data set, as this would allow me to use a ‘large’ data set on crying, rather than having to create one from scratch and only have the time to create a small data set. However, whilst developing concepts, I realised that I missed the personal connection to the data and that certain aspects –the more qualitative aspects, such as the emotion behind the cry– were missing. Therefore, I tracked my own crying data, based on the categories created by Weis. To this I added the emotion behind the tears, and left out the time and duration of the cry, as I wanted to focus on the experience—not tracking the data. This resulted in the following set of 8 cries:
Whilst creating this data set, I started to think of what a physicalisation of cries would look like. During my presentation, I already stated that: “I don’t want to design a fountain”. Although I must admit that this would be fun, it felt too ‘easy’ and I wanted to challenge myself by imposing the limitation of not representing tears through water. Instead, I decided to focus on the idea of tears leaving our body and brining those tears back, which inspired me to create a data physicalisation which you can eat : where the cries are communicated through taste and texture. Thus the question became, what do tears taste like?
A small background on the taste of tears:
Our tears are composed of water, oils, proteins, and electrolytes, such as sodium and potassium . Due to the electrolytes, tears have a salty taste. There are 3 types of tears: basal/continuous, reflex, and emotional tear . The emotional tears ‘flush out’ stress hormones, whilst at the same time releasing hormones which make you feel better, such as endorphins. Because of this composition, emotional tears are the least salty .
Based on the background research, I decided to create chocolate bonbons (chocolate contains endorphins after all), to represent my 8 crying episodes. The bonbon would consist of a ganache and a galette. Each galette is made by boiling glucose syrup and chocolate to 145 degrees Celsius, pouring the liquid on a piece of baking paper to let it cool down, after which it is blended till a powder, which can be evenly distributed using a sieve. The shape and size of the galette would represent the intensity of a cry. The taste of the ganache and galette represents the emotion (Figure 1).
However, an experiment with the galette showed that I could not control the shape: the galette melted and expanded in the oven; even after freezing it first (Figure 2). Therefore, I decided to focus on the texture of the galette to represent the intensity, where I based the texture on conceptual metaphors (e.g., rough is bad, in this case angry) . Besides texture, I would further use the intensity of the taste to represent the intensity of the cry. Thus, both the texture and intensity of the taste represent the intensity of the cry.
The taste of the bonbons represents the emotion of the cry, for which I was inspired by a blog post, which states that the chemical composition of tears changes their taste: angry tears would consist of a lower concentration of moisture and have a higher sodium concentration (thus being saltier), sad tears taste more acidic, and happy tears are supposedly sweeter . I could not find scientific papers to back up these statements. Therefore, this only served as inspiration and is not something I consider to be proven.
Inspired by this, I created the following mappings:
|Angry||Very salty. As anger is often associated with heat, these bonbons contain chilli to make them spicy. The base of the bonbons is dark, bitter chocolate (80%).||Rough|
|Sad||Salty and acidic, through a higher concentration of lemon juice in the home made glucose syrup. The bonbons are based on milk chocolate, so they are less bitter than the angry tears.||Less rough, by baking it at a lower temperature. However, the texture is still perceivable when eating the galette.|
|Happy||Sweet and salty, the bonbons are based on white chocolate for intense sweetness.||Glossy and smooth|
This mapping was applied to the bonbons, which consist of: (1) a ganache base, made of the respective chocolate (white=happy, milk=sad, pure=angry), salt, and in case of angry, chili, and (2) a chocolate galette made of sugar, the respective chocolate, and home made glucose syrup. The glucose syrup was made by boiling water, sugar, and lemon juice to a 118 degrees Celsius, which allowed me to control the acidity levels. Overall, I created the following bonbons per emotion:
Together these bonbons resulted in the following overall data physicalisation:
1. Nicholas M. Farandos, Ali K. Yetisen, Michael J. Monteiro, Christopher R. Lowe, and Seok Hyun Yun. 2015. Contact Lens Sensors in Ocular Diagnostics. Advanced Healthcare Materials 4, 6: 792–810. https://doi.org/10.1002/adhm.201400504
2. Florian ’ Floyd’ Mueller, Sarah Goodwin, Han Phan, Rohit Khot, Kim Marriott, Jionghao Lin, Yan Wang, Tim Dwyer, Jialin Deng, Kun-Ting Chen, and Kim Mar-Riott. Data as Delight: Eating data; Data as Delight: Eating data. https://doi.org/10.1145/3411764.3445218
3. William H. Frey, Denise Desota-Johnson, Carrie Hoffman, and John T. McCall. 1981. Effect of Stimulus on the Chemical Composition of Human Tears. American Journal of Ophthalmology 92, 4: 559–567. https://doi.org/10.1016/0002-9394(81)90651-6
4. Jörn Hurtienne, Christian Stößel, and Katharina Weber. 2009. Sad is heavy and happy is light. In Proceedings of the 3rd International Conference on Tangible and Embedded Interaction – TEI ’09 (TEI ’09), 61. https://doi.org/10.1145/1517664.1517686
5. Yvonne Jansen, Pierre Dragicevic, Petra Isenberg, Jason Alexander, Abhijit Karnik, Johan Kildal, Sriram Subramanian, and Kasper Hornbæk. 2015. Opportunities and Challenges for Data Physicalization. In Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems, 3227–3236. https://doi.org/10.1145/2702123.2702180
6. Eunah Lee Kwon. 2008. Different Tears Different Taste. University Newspaper. Retrieved from http://smtimes.sookmyung.ac.kr/news/articleView.html?idxno=286
7. Robin Weis. 2016. Crying. Retrieved from http://robinwe.is/explorations/cry.html