Executive Summary

Shop data provides an invaluable look into the bigger picture of a city’s economic status. Being the main contributors to the production of goods and services in an economy, shops can act as an economic indicator. In the case of Venice, Italy, tourism plays a big role in its economy as approximately 25% of shops cater toward tourists alone. This socially excludes local Venetians and causes a divide between them and visitors.

However, for the first time in history, tourists are no longer able to visit the

city due to the COVID-19 pandemic. Because of this, Venetian commerce has been greatly affected.

In order to see how Venice’s economy has been affected, it is imperative to understand and visualize its commerce history, which has been quantified for over 15 years by the VPC. Starting in 2004, eight WPI teams have collected shop data from various sestieri all over Venice, taking note of attributes such as shop names, addresses, and geographical location.

For our project, we worked with our sponsors SMARTDEST and SerenDPT. The former is a research project focused on social exclusion and more recently, the sustainable return of tourism to European cities post COVID-19, and the latter is a Venetian start-up organization in charge of the Venice case study of the SMARTDEST project.

With their help, we have built a web application from the ground up that can visualize the history of Venetian commerce.

In order to do this, our team found, consolidated, and cleaned eight datasets on shops. This process took all previously recorded shop records, 11,312 to be exact, and unified them into one collective dataset, which now houses all shop data ever collected by the VPC. This work was done remotely, over the course of seven weeks, with the help of our advisors, Professors Fabio Carrera and Jennifer deWinter.

Our dataset houses three subsets of data, “Venice Shops”, “Store Locations”, and “Venice Shops Images”.

The “Venice Shops” dataset houses information on the name and type of a shop while the “Store Locations” dataset contains information on a shops location. This includes its address, which Sestiere its located in, and its longitudinal and latitudinal coordinates. Lastly, our team also found and consolidated any and all photos of shops and stored them in our “Venice Shops Images” dataset.

Once cleaned, this data was then visualized on our web application. It allows users to filter shop data by the year the data was collected, the type of shop, as well as filter shops by their target audience.