Gluten Free Map of North End

Experience the Interactive Map

Printable Map

About the Project

Audience: People who are gluten free and trying to visit the North End of Boston

Tools Used: Storyline 360, Mindmiser, Canva, Google Suite

What is the North End and why is it difficult for Non-Gluten Eaters?

The North End of Boston is an Italian neighborhood known for its delicious food options. You can find amazing arancini, freshly baked bread, cannolis fried to order, and homemade pasta made in-house. However, due to the abundance of gluten in many of the food options, it can be challenging for those with gluten sensitivities.

Why the map?

The North End is a small neighborhood within Boston, which is not a large city in terms of area. I included a map to help people visualize the easy accessibility of the area. The majority of the restaurants and shops are located on two parallel streets: Hanover and Salem Street. These streets were the primary focus of my project as they are where the majority of the food options can be found.

Experience the Interactive Map

The Different Sections

I divided the map into sections to make it easier for people to find specific types of food. For example, if someone is only looking for desserts, they can easily access that information without having to sift through all the locations. I also included information on parking and bars, which may be helpful to anyone, not just those with gluten sensitivities.

Sources

I researched each restaurant's menu and consulted with someone who has Celiac Disease, who has extensive knowledge of the North End's food scene. Using these resources, I created this map to showcase the best places for gluten-free options and provided information on what items are particularly good at each location.

Hand Out

I have included a PDF map of all marked locations, which was created using Google Docs and Canva. Canva was used to create a variety of icons to easily distinguish the types of places on the map. My main challenge was identifying different locations on the map. To solve this, I used a numbering system and different colors to differentiate between the types of locations.