This project’s mission is to provide a web-application tool that visualizes and analyzes trends in Venetian Commerce over time by organizing archival data provided by the Venice Project Center (VPC). The WPI students have deployed a platform that future collaborators will be able to iterate on to help assess Venice’s economy.
These are their main objectives:
- Consolidate data that was previously collected on Venetian stores
- Design and test a comprehensive and flexible web-application
- Analyze archival WPI data on Venetian commerce
- Plan for the future of the web application
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 this project, a team of VPC students worked with SMARTDEST and SerenDPT. The latter is a Venetian start-up organization in charge of the Venice case study of the SMARTDEST project. With their help, a web application was built from the ground up. This app permits to visualize the history of Venetian commerce.
In order to do this, the 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 their advisors, Professors Fabio Carrera and Jennifer deWinter. The dataset houses three subsets of data, “Venice Shops”, “Store Locations”, and “Venice Shops Images”. Lastly, the students 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 the 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.
Curated by Giulia Speri