In order to reduce poverty and improve people’s lives everywhere, territorial development must be sustainable. Data science and analytics can offer fundamental contributions to it. Moreover, to achieve the 17 goals in the 2030 Agenda for Sustainable development defined by United Nations, citizens’ participation in decision processes is paramount. Indeed, it helps fight against corruption and facilitates the policymakers aligning their decision with the needs of citizens. The research described in this thesis has two main objectives, namely to harness Big Data for sustainable spatial development and to promote citizen involvement in decision-making processes by offering them a new tool for geovisual analysis of spatial data. The growing number of devices and people connected to the Internet are valuable sources of geographically localized information, not yet fully exploited. Although this data has all the characteristics of the Big Data for the Sustainable Development, as defined by United Nations, it requires innovative architecture and tools to be managed. Furthermore, citizens’ involvement requires that these tools should be simple to use and understand, even during complex data analyses. The dissertation describes the research that led to the layered framework that helps leverage Big Data for Sustainable Development, and the new visual tool that helps citizens participate in data analysis. [edited by Author]