Development of infrastructure for integration and improvement of accessibility of socio-environmental data and support to public policies

• Grant number: 23/00779-0
• Support Opportunities: Regular Research Grants
• Start date: August 01, 2023
• End date: July 31, 2025
• Field of knowledge: Physical Sciences and Mathematics - Computer Science - Computer Systems
• Agreement: MCTI/MC
• Principal Investigator: Kelly Rosa Braghetto
• Grantee: Kelly Rosa Braghetto
• Host Institution: Instituto de Matemática e Estatística (IME). Universidade de São Paulo (USP). São Paulo , SP, Brazil
• Associated researchers: Aluízio Marino ; Denis Deratani Mauá ; Sarajane Marques Peres ; Tiago Silva da Silva ; Vitor Pinheiro de Almeida
• Associated scholarship(s): 25/02535-6 - Geocoding of socio-environmental databases using open tools and maps, BP.TT; 24/07276-6 - Geocoding of socio-environmental databases using open tools and maps, BP.TT; 24/07305-6 - Implementation of integration and consultation infrastructure for socio-environmental data, BP.TT

Abstract

The CulturaEduca portal (https://www.culturaeduca.cc/) is a collaborative mapping platform for storing, analyzing, and georeferencing data. The platform particularizes socio-environmental data from official sources on an intra-urban scale, provides data from public policy units, and incorporates data from civil society agents who experience the territory. To enable the platform's growth and enhance the reuse of its data, this project proposes the development of free software to integrate open socio-environmental data on a large scale and with advanced resources for describing and querying data. The development of this infrastructure involves several technological and scientific challenges due to the characteristics of the databases of interest (e.g., large volume, heterogeneity, and dynamics) and the different profiles of users and applications the platform aims to serve. To address these challenges, this project will develop research in the areas of Database, Knowledge Representation, Machine Learning, and Smart Cities. In particular, the project will develop mechanisms for metadata management and semantic enrichment of databases to facilitate complex queries and knowledge discovery. It will also develop innovative tools to simplify queries on spatial and temporal data for non-technical users, such as database query interfaces based on natural language. With this, we expect to expand access and accessibility to strategic data for planning community actions and supporting public policy-making. (AU)