OpenStreetMap in the Training of Local Actors in Projects Aimed at Community-Based Interventions in Slums: A Systematic Review Supported by AI

This text aims to analyze the process of training residents from peripheral communities in the use of free geospatial tools, with a special emphasis on OpenStreetMap (OSM). The analysis is based on a literature review, conducted with the aid of generative artificial intelligence tools, seeking to understand the impact of these initiatives in favelas. The primary focus is to explore how the use of OSM, as the world's largest collaborative mapping tool, is utilized for community mobilization, promoting digital inclusion and geospatial knowledge acquisition. Additionally, it highlights the main challenges faced by these initiatives, including an analysis of studies conducted in communities and the continuous engagement of participants. The text also seeks to identify gaps observed in the reviewed literature, pointing out future directions for research and interventions that can further enhance the social and transformative impact of these collaborative mapping tools in favelas.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2024-12-02
DOI
https://doi.org/10.5281/zenodo.14250653
Primary Topic
Geographic Information Systems Studies
Type
article
Field-Weighted Citation Impact
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article

OpenStreetMap in the Training of Local Actors in Projects Aimed at Community-Based Interventions in Slums: A Systematic Review Supported by AI

Zenodo (CERN European Organization for Nuclear Research)
Geographic Information Systems Studies
article

OpenStreetMap in the Training of Local Actors in Projects Aimed at Community-Based Interventions in Slums: A Systematic Review Supported by AI

article en

Abstract

This text aims to analyze the process of training residents from peripheral communities in the use of free geospatial tools, with a special emphasis on OpenStreetMap (OSM). The analysis is based on a literature review, conducted with the aid of generative artificial intelligence tools, seeking to understand the impact of these initiatives in favelas. The primary focus is to explore how the use of OSM, as the world's largest collaborative mapping tool, is utilized for community mobilization, promoting digital inclusion and geospatial knowledge acquisition. Additionally, it highlights the main challenges faced by these initiatives, including an analysis of studies conducted in communities and the continuous engagement of participants. The text also seeks to identify gaps observed in the reviewed literature, pointing out future directions for research and interventions that can further enhance the social and transformative impact of these collaborative mapping tools in favelas.

Zenodo (CERN European Organization for Nuclear Research)
Universidade Federal da Bahia (BR)
Reduced inequalities
Openalex Percentile: Top 34%
Geographic Information Systems Studies
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