FoodScapers Proposal

ABOUT US

PROPOSAL

POSTER

APPLICATION

RESEARCH PAPER

Problem and Motivation

Singapore is well known for its diversity and fusion of food, with influences from the Chinese, Indians, Malays, to the French and even Italian. Interesting, this unique blend of authentic Singaporean food can only be found in Singapore. More often than not, restaurants in present-day Singapore can be seen serving fusion food inspired by Singapore’s diversity. Instead of having the differences divide the country, Singapore’s diversity serve as a spark to Singapore’s unique melting pot of food culture.

Through our visualisation, we hope to represent the distribution of food diversity throughout Singapore. In particular, we would dive deeper to uncover what makes a specific location a food paradise for a specific race, the purpose behind the food stalls and the price elasticity of food.

Objectives

This project aims to bring insights into the distribution of food across Singapore (by Operators) by tackling the following topics:

1. Exploring the Correlation between food and location (Food identity across Singapore)
2. Differentiating restaurants by “Local Haunt” or “Tourist Trap”
3. Mapping the “Atas” Local Food Trend
4. Visualising the Price Elasticity of Food by Dish
5. Mapping Singapore Food by Day & Night

Related Works

Visualizations	Explaination
Yelp Insights : Data Visualization Source: http://shirleylei.com/projects/yelp.html	Shirley Lei's work on Yelp's Restaurant Data, uses Tableau as a visualisation platform to draw correlations between the neighbourhood the restaurant is in, the primary attributes of each restaurant (type of cuisine, outlet type, etc.), and the secondary attributes of each restaurant (WIFI and Child-friendly category tags).
Is Dirty Delicious? Source: https://blog.data.gov.sg/is-dirty-delicious-f176bbb6e15e	Lin Zhaowei & Gaille Teo's work on visualising cleanliness ratings of hawker stores, combines both Yelp's Restaurant Ratings Dataset, as well as NEA's cleanliness score dataset, to draw parallels between a store's cleanliness rating, and Yelp user review ratings. The results attempt to debunk a common misconception that 'dirtier' hawker stores are reviewed better.
[[	550px|center]] From Hawaii to the Heartland: Poke’s journey from local favorite to food craze to national staple Source: https://www.yelpblog.com/2018/08/pokes-journey-from-local-favorite-to-national-staple	Carl Bialik is a Data Editor at Yelp. In this work, he uses data visualisations to tell a story of the rapid rise in popularity of Hawaiian Poke between 2013 and 2018. By visualising the rise of Hawaiian Poke over time, in relation to the popularity of other food categories allow users a better context of the American food landscape, one in which the Hawaiian poke is an outlier.

Datasets and Sources

We need a vast dataset that covers the various aspects of dining in Singapore, and for this reason, we have chosen the following data sources to obtain a rich dataset.

1. Postal Codes - List of all possible postal codes where a restaurant/hawker centre could exist within Singapore. Retrieved from OneMap API:
2. Possible Restaurants of Interest - List of all restaurants that exist on the yelp portal at the postal codes provided. Retrieved from Yelp API:
3. Restaurant Details - Details posted on yelp for the restaurants of interest. Retrieved using a crawling and scraping script on the Yelp Website.
4. Patron Reviews and Patron Details- Comments and reviews regarding the patrons' experience at the specific restaurant. Additionally, public details about the patron were obtained. Retrieved using a crawling and scraping script on the Yelp Website.

Below is the list of Table Header name, description and an example for each table.

1. Postal Codes: Retrieved in JSON format using the OneMap API. Only showing attributes used.
Source : http://developers.onemap.sg

Name	Description	Example
Address	Full address of the Postal Code	"7 MAXWELL ROAD AMOY STREET FOOD CENTRE SINGAPORE 069111"
Coordinates	Latitude and Longitude of the Postal Code.	{ "latitude": 1.28035, "longitude": 103.84472 }

2. List of Restaurants at a postal code: Retrieved as a JSON Array. Only showing attributes used.
Source : https://api.yelp.com/v3/businesses/search?location=069120

Name	Description	Example
id	Unique ID of the restaurant.	"fY1IkBnRft1KR0O2tqu7pg"
Name	Name of the restaurant.	"Tian Tian Hainanese Chicken Rice"
URL	URL of the of the restaurant's yelp page, used for web scraping.	https://www.yelp.com/biz/tian-tian-hainanese-chicken-rice-singapore-7
Categories	Type of Restaurant.	"Hainan"

3. Restaurant Details: Retrieved using Python and returned in JSON format
Source : https://www.yelp.com/biz/din-tai-fung-singapore-5?osq=Din+Tai+Fung

Name	Description	Example
Name	Name of the Restaurant	Din Tai Fung
Location	Address at which the restaurant is located	Wisma Atria 435 Orchard Rd Level 4 Singapore 238877 Singapore Orchard
Opening Hours	Opening Hours of the restaurant	11:30 am - 10:00 pm
Cuisines - Menu	Cuisines offered by the restaurant	Taiwanese, Dim Sum
Expected Attire	Attire expected of patrons when visiting the restaurant	Casual
Price Range	Price Range of food offered by the restaurant	$$ later converted to a price bucket
Rating	Average Overall Ratings provided by the patrons	4.5 stars
Reviews	Number of Reviews regarding the restaurant	116

4. Patron Details and Reviews: Retrieved using Python and returned in JSON format
Source : https://www.yelp.com/biz/din-tai-fung-singapore-5?osq=Din+Tai+Fung

Name	Description	Example
Name	Patron's Name	Bob B.
Location	Patron's Hometown	Houston, TX
Rating	Patron's rating awarded to the restaurant	5 stars
Review	Patron's review of the restaurant	The Best Dim Sum / steamed dumpling and noodle restaurant in the world. This restaurant is located in a hotel lobby. It is Hands down the best. Be prepared to wait because the lines are always long but when you receive your order it will be well worth it. They have an old style tradition so you take a number and wait. You will receive a pencil and a menu to check the items you would like to order and your party number before you are seated. Once a table is available your order will arrive and the eating will start while they continue to bring your table the freshest of authentic Dim Sum imaginable. This restaurant was #1 in Hong Kong. We ordered multiple dishes and they all were the best we ever have. This restaurant is world famous after eating here I understand why we enjoyed many dishes to many to name but it was all amazing. Sliced Chicken Noodle Soup Shrimp Fried Rice Shanghai Rice Cakes with Shrimp steamed garlic spinach Dim Sum steamed broccoli and the best of anything they provided it was all and all a 5 star experience.

Based on the retrieved data, we will do data cleaning and entity extraction in order to understand some of the dishes on the menu and their cost (if available).

Storyboard

WIP

Tools/ Libraries

WIP

Timeline/ Roles

WIP

Ideation Drafts

This section is updated based on meetings and the ideation process behind the visualization that will be our final output.

Data of Essence to our visualization: An attempt to select relevant variables from the data rich source that is yelp

Storyboard objectives: An attempt to clarify and narrow our scope

Challenges and Assumptions

The challenges we face include:

No.	Challenges	Description	Proposed Solution
1.	Data Cleaning and Transformation	The data collected under the patrons' reviews is generally representative of the patrons own characteristics and often includes their cultural identity through fillers like lah, as well as spelling errors, that can make entity recognition difficult.	Use of a dictionary and spell check tool to improve the quality of the data to ensure entity recognition is successfully applied
2.	Information Presentation	Determining the most effective way to visualise and display the data in an interactive format is of the essence. It is necessary that the most important information is easily discernible from the visualisations.	Gain exposure to different visualisation techniques. Follow and revisit techniques explored in class. Also look at DataCamp courses.

The assumptions we made include:

1. If data regarding a restaurant is not available on yelp, we assume that the restaurant is not popular i.e. not much footfall reaches the restaurant. Therefore the restaurant would not add much value to our visualisation.

References

WIP

Comments

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