Coming Soon
is a local Vietnamese restaurant, close to our office. Along with
wonderful food, they also provide a cultural hub for local artists. Part of the
restaurant is a large vintage poster board that offers a creative platform to
showcase local businesses. We were approached to exhibit our work in April 2020
and decided that this would be an excellent opportunity for an internal lab
project that could explore data about the restaurant through a large printed
visualization. Together with Annina and Christian, we were excited to kick off
the project and explore the story behind the data.
Research & Design Iteration
Like most of our projects, we started with a thorough brainstorming session and plenty of sticky notes and markers to quickly get our ideas and impressions down for the team to see. We collected our thoughts and started organizing them into bins so we could see the directions to explore. Researching brought up lots of inspirational work as well as clarifying the data we would need to collect for our ideas. We started our ideation with quick sketches that framed our ideas and represented the data in a way that tells a story and provides insight or understanding.
Eliminating ideas that might be out of scope or in the wrong direction and instead focus down on a few ideas that we see having the most potential. Diving deep into the narrower selection, we explored what we needed to produce them with data, as well as what kind of resources we needed to collect or allocate for production.
By the end of our design ideation, we had focused down on two ideas to explore. The first was based on the concept of a decision tree, something that would help customers to decide what dish to order or try something new. The second was a more thorough breakdown of a single dish, overlaying graphical elements that represent the data and focusing more on the visual representation, rather than the tooling. Before we could make a decision, it was important to build these examples using actual data and assets so we shifted our attention towards the dishes themselves.
Pop-Up Photoshoot
Both of the designs were in part inspired by the graphical styles from our
initial research. Specifically, the work by Ryan MacEachern on
Food x Design
1 and Yum Tang on SHUSHI
2 has great visual appeal and fit
nicely with the vibrance and complexity of the dishes. We partnered with a local
video/photographer, Natalia Kobylinksa, and set up a photoshoot of the dishes.
Together with Coming Soon, we built a pop-up photo studio inside the restaurant
and, during their dinner rush, seamlessly photographed every dish on the menu as
they were being ordered.
Our next step was to clean and colour correct the images so we could use them in
our designs. Thanks to some very clever machine learning tools from
Kaleido AI
3, we were able to remove a lot of the backgrounds fairly
effortlessly and then use them in photoshop to create perfect images for our
ideas.
Exploring the Data While we collected photo assets, we organized the information provided by Coming Soon as well as added additional data through researched or scrapping. For the decision tree idea, this involved creating nested datasets of the menu categories, items, and their components. We first built tabular datasets using excel and then imported into D3.js which could be used to restructure the data and visualize it as a force tree diagram. From here we could organize the data in different categorizations to look at how the decision tree could be graphically represented on the board.
The second idea, breaking down an individual dish, required much more information about the dish themselves and so we gathered information of their sales and popularity for the last year as well as a breakdown of their ingredients. By combining the information collected with the USDA's FoodData Central4 we could build detailed nutritional tables for each dish in Tableau. Tableau also allowed us to visualize layers of the information to see trends or patterns and create quick graphs to test with our concept.
Layering the Data
With the data and the pictures in front of us, we were able to identify problems and potential focus from our initial ideas. We realized that while the force tree diagrams for the decision tree were interesting looking and fun to explore on a computer when it came to a large print we quickly lost the essential beauty of the photographs when so many were on the board at once. We could see that the individual breakdown offered much more interesting insight into the dishes and invoked the most intrigue for further exploration. From here we could start to design the final layout, working with proportions and typology to best represent and highlight the data.
Working first with Tableau and Illustrator we created many different graphical styles for the data, representing different relationships or focusing on different topics. Similar to our initial design process, we quickly saw what ideas work and which created confusion. We focused on representing the nutritional information of each dish/ingredient in a way that allowed you to compare them easily as well as highlight interesting nutritional facts. We created a stacked radial graph for the nutrition of each ingredient that proportionally sized itself around the dish based on its weight like a pie chart, to create a stacked radial pie chart. Building this in D3.js allowed us to quickly experiment and format the atypical graph structure and refine its proportions and layout with feedback from the design.
Graphical Production
From our D3.js code, we extracted SVG files that imported directly into Photoshop to be combined with our cleaned photos and layout. With a bit of back and forth, we were able to quickly test ideas and produce polished designs for review. With the posters being so large, we came up with a hybrid method of testing the ideas on a projector to get a feel for the proportions of the design as a whole while at the same time test printing smaller components to ensure adequate readability and accessibility. With our final design reviewed, refined, and approved we were ready to start printing. Working with a local print shop we tested colours and quality and make any final adjustments before sending the final proof to print.
We hope you have enjoyed reading about our process in producing this project. With the pandemic going on, we hope to have the first edition up in May 2020. Coming Soon will be reopening their doors May 11th and will be displaying a slightly smaller version in their store window until times when they can return to normal business.
Footnotes
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Maceachern, Ryan. “Design x Food.” Issuu. Accessed January 29, 2020. https://issuu.com/ryanmaceachern/docs/designxfood. ↩
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Tang, Yum. “‘SHUSHI.’” Edited by WildAid. Behance. Accessed January 22, 2020. https://www.behance.net/gallery/72884621/SHUSHI. ↩
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Kaleido. “Remove Background from Image.” remove.bg. Accessed February 24, 2020. https://www.remove.bg/. ↩
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“FoodData Central.” FoodData Central. Accessed February 25, 2020. https://fdc.nal.usda.gov/. ↩