NYCFOODIVERSE is a data visualization experiment that provide immersive data exploration experience on all the restaurants in the Manhattan area, NYC.
It combines data from NYC Department of Health and Foursquare ratings to show restaurant grades, sanitation scores, violations, price tier, reviews and much more.
The visualization integrates data from two data sources NYC Health Inspection Data and Foursquare rating.
This data includes location information of restaurant along with the inspection details like the inspection date, violation code, violation description, grade, score and inspection type.
Foursquare rating provides ratings for restaurants on ten-point scale based on user feedback. This data is gathered using the Foursquare API.
The target audience of this visualization is the general public which includes either the residents of the Manhattan area or the travelers to this area looking for a quality restaurant.
In the words of the developer Will Su “Social media food ratings are difficult to parse and generalize…”, thus this visual experience alleviates this problem by helping people not only to determine the popular restaurants but also allow them to see the sanitary conditions of the restaurant, pricing and reviews.
The visualization is divided into three sections: Foodiverse | Graph | Map | Search
This section consists of text block of violation codes in the center which corresponds to one sanitation violation. For instance: Code 06D represents Food contact surface not properly washed after each use and following any activity after contamination may have occurred.
The points around the violation codes represents one restaurant in Manhattan. And the color codes depict the current Grade level which is on the basis of NYC Food Inspection rating as detailed below:
Grade A: 0-13 points
Grade B: 14-27points
Grade C: 28+ points
In addition to that an option has been provided for changing the color of data points by the last time inspection.
The data points location is assigned by force directed graph drawing algorithms.
Towards the right is a section which provide further insight into the point which is highlighted (point can be restaurant or the violation code).
Hovering on the violation codes highlights all the restaurants with that sanitary violation and the right section displays the number of restaurants that contains this problem. Further clicking on it expands the right section which details the problem and provides a list of restaurants that have this problem.
Hovering over the restaurant point highlights the sanitation problems of the restaurant. Also, clicking the restaurant point expands the right section. It includes details like:
This section shows the data as scatter plot where X axis is the Sanitation Score and Y axis can be changed to either Foursquare rating or
the Price Tier.
When the user hovers over the point, all the overlapping restaurants are revealed.
This section places the data on the map and has been color coded by the recent grade of the restaurant. The size of the circles represents the Sanitation Score. In addition to that on the left links have been provided to common places like Chinatown, Little Italy, Downtown and others.
The search field allows the user to compare multiple restaurants by plotting data on line chart.
Using this visualization solution, the user can find answers to the following questions:
|Which are the top 10 filthiest restaurants New Yorker’s love the most?||In the Graph section, top right represents the dirtiest restaurants with highest customer ratings.|
|Comparison of two or more restaurants.E.g. How Rao’s compares to Karaoke Wow! In price and reviews?||Using the search box, the user can look up for the restaurants and compare them using line chart which show historical inspection record of one year. Also, the right panel provides the details.|
|Which are the cheapest and cleanest restaurants?||In Graph section using Price Tier as y axis, the bottom left shows the restaurants which are cheapest and cleanest.|
|How many restaurants violated particular code like 10F?||Hovering over the code shows the description and number in right panel. Clicking on it displays the list of restaurants that violated the code.|
|Which restaurants are in Little Italy?||Using the map, the user can locate the restaurants nearby along with their details.|
On the whole, this is a good solution to visualizing the relationship between the restaurant inspection data and customer ratings. Along with having all the features that a usual restaurant rating website has; this visualization extends the user experience by also incorporating the food inspection data and allowing the user to explore the data using multiple views.