Visualizing the quality of life in the city of Genoa

Abstract

Nowadays, innovative tools are needed to assist policymakers in addressing urban challenges and improving the quality of life for citizens. This is due to the increasing complexity of urban environments. My thesis presents the design and development of an interactive dashboard for visualizing the quality of life in the city of Genoa. During the dashboard development, I used data visualization techniques, such as choropleth maps, clustering techniques, and dynamic bar charts. This was done to provide actionable insights into demographic distributions, human development indices, and the spatial availability of services such as pharmacies and sports facilities.

I extended the dashboard using the D3.js JavaScript library to integrate demographic and socio-economic data with urban infrastructure analytics, offering users a customizable interface for filtering and exploring key urban indicators. The clustering of services, which is dynamically adjusted to zoom levels, reveals patterns of inequality in resource distribution, highlighting underserved areas and enabling data-driven decision-making. The developed control panels allow decision-makers to query data by selecting specific factors, such as job categories, family size, or human development levels, creating highly tailored visualizations for in-depth analysis.

The findings of this project demonstrate the potential of interactive dashboards as decision-support systems for urban governance. The dashboard represents complex urban data in an accessible format to empower decision-makers with the tools to identify development gaps and implement targeted interventions. Our dashboard focuses on the city of Genoa, but the methodology used is scalable and adaptable to other urban areas and cities, clearing the way for further research into integrating advanced analytics, real-time data, and predictive modeling into urban planning tools.

Nowadays, innovative tools are needed to assist policymakers in addressing urban challenges and improving the quality of life for citizens. This is due to the increasing complexity of urban environments. My thesis presents the design and development of an interactive dashboard for visualizing the quality of life in the city of Genoa. During the dashboard development, I used data visualization techniques, such as choropleth maps, clustering techniques, and dynamic bar charts. This was done to provide actionable insights into demographic distributions, human development indices, and the spatial availability of services such as pharmacies and sports facilities.

I extended the dashboard using the D3.js JavaScript library to integrate demographic and socio-economic data with urban infrastructure analytics, offering users a customizable interface for filtering and exploring key urban indicators. The clustering of services, which is dynamically adjusted to zoom levels, reveals patterns of inequality in resource distribution, highlighting underserved areas and enabling data-driven decision-making. The developed control panels allow decision-makers to query data by selecting specific factors, such as job categories, family size, or human development levels, creating highly tailored visualizations for in-depth analysis.

The findings of this project demonstrate the potential of interactive dashboards as decision-support systems for urban governance. The dashboard represents complex urban data in an accessible format to empower decision-makers with the tools to identify development gaps and implement targeted interventions. Our dashboard focuses on the city of Genoa, but the methodology used is scalable and adaptable to other urban areas and cities, clearing the way for further research into integrating advanced analytics, real-time data, and predictive modeling into urban planning tools.