Rhythm of Food is an open project started by Google News Lab and Truth % Beauty. This project shows Google search trends of food over the years, as a year clock. The project team insists that there is a consistency in trend in different types of food that can be investigated through data from Google search.
The goal of the project is to show how the search trend for food has changed throughout 15 years, in one diagram. The project contains year clock diagrams based on type of food, month year, seasons, and etc. Anyone in the public is able to go through the website to look at the trend by clicking on the category which they want to see the trend for.
If the user clicks on the button which says “summer”, the user would be able to look up which food has the most search in the season of summer. Let’s see what they show.
When the user presses the category of summer, the user is able to see year clocks for food which are searched frequently during the summer. The user can click on the year clock to see more detail about each food and its “rhythm”.
When the user presses the play button, the search trend from year 2004 to 2018 shows up on the clock. The description on the right explains when people search for this food, and the year trend in a line graph.
Sources : According to the project, all of the Google search data came from Google Trends, and the team used Google Knowledge Graph topics, focusing on data from the United States. The website includes 201 topics and presents 155,705 individual data points.
Processes: The individual data points were analyzed and organized by month, season, and food related categories.
Presentation: The website includes year clocks and graphs with color scheme, helping the user understand the data more easily.
I have some questions left even after breaking down this project. How did the team decide which categories they would add on the website? Were there any outliers in the search trend of a certain kind of food? What kinds of unexpected issues or incidents might have affected an outlier in some of the search data?
I think you bring up an interesting question in relation to outliers in the data. In the video that you showed, the data seemed to follow a similar pattern through the years along with an increase in searches. It would be interesting to see how the production of the food items over the years might map onto these already existent data sets. How does the popularity of these items impact other efforts, such as the production of these food items?