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UID:pretalx-foss4g-2024-academic-track-HMEXFV@talks.staging.osgeo.org
DTSTART;TZID=-03:20241204T161500
DTEND;TZID=-03:20241204T164500
DESCRIPTION:Public participation is of utmost importance for community mobi
 lization and engagement\, so that through their networks and relationships
 \, both within and outside the community\, they create space through socia
 l action. According to Goodchild (2007)\, there is a demand to generate in
 formation that helps vulnerable communities to strengthen relationships wi
 th the government responsible for promoting important interventions to bri
 ng about change. It is possible to use the sensitivity and ability to info
 rm the needs of each resident\, from their perception\, and understand the
  needs of their community. Therefore\, it is important to use open and fre
 e mapping tools that represent the community's demands\, producing informa
 tion that allows collective autonomy to carry out strategies that involve 
 the public authorities through co-optation and coalitions aimed at communi
 ty-based interventions (Silva\, 2014).\n\nIn this sense\, OpenStreetMap (O
 SM) stands out as a tool for collaborative mapping and community intervent
 ions in highly vulnerable urban areas\, such as favelas. Given OSM's parti
 cipatory and open nature\, it allows the creation of maps with records of 
 features of various kinds\, but it is also of great value as a platform fo
 r community training and the development of geospatial skills (Bortolini a
 nd Camboin 2019).\n\nThe objective is to analyze from the literature how O
 penStreetMap has been used for training and empowering local actors in pro
 jects aimed at community-based interventions in favelas.\n\nA systematic l
 iterature review was carried out with the support of artificial intelligen
 ce tools (Chat GPT-4\, Elicit\, Semantic Scholar\, Chat pdf)\, bibliograph
 y management software (Zotero)\, and software for visualizing bibliometric
  networks (VosViewer) combined with other research methodologies (P.I.C.O.
 \, Bardin) to assist in the overall evaluation of the literature. Although
  AI tools have great power to aid the review\, they do not replace the nee
 d for critical judgment and human expertise\, demanding confidence in the 
 knowledge of the contents and scientific methodology.\n\nThe following key
 words were used in the platforms of WoS and Scopus collection lists in the
  first search: [Collaborative mapping\, Community intervention\, OpenStree
 tMap\, Community empowerment\, Community mobilization\, Citizen participat
 ion]. In this first search\, some filters were established\, such as the p
 ublication date within the last 10 years and articles that were open acces
 s. Based on these filters\, 43 articles were found that fit these specific
 ations in the Web of Science\, with the vast majority in English. From thi
 s first literature search\, there also arose the need to increase the numb
 er of articles that most closely aligned with the theme. The keywords were
  adjusted based on these articles. In this second search\, other databases
  were also included for the research\, such as Scopus and Google Scholar. 
 The use of artificial intelligence tools Elicit and Semantic was essential
  to find articles using the keywords that were most repeated in the main a
 rticles. Still in this second search\, these adjusted keywords were entere
 d into Chat-GPT 4 to generate search strings under the acronym P.I.C.O (Po
 pulation\; Intervention\; Comparison\; Outcome) for use in the Web of Scie
 nce.\n\nKeywords for the second search: [Collaborative mapping\, informal 
 settlements\, urban slums\, OpenStreetMap\, public participation\, communi
 ty engagement\, community-based intervention\, community intervention].\nF
 inal search string: [("Collaborative mapping" OR "participatory mapping") 
 AND ("community intervention" OR "community-based intervention") AND ("Ope
 nStreetMap" OR OSM) AND ("community empowerment" OR "empowerment") AND ("c
 ommunity mobilization" OR "community engagement") AND ("citizen participat
 ion" OR "public participation") AND (favelas OR "informal settlements" OR 
 "urban slums")]. Finally\, twenty articles were identified in the Web of S
 cience\, Google Scholar\, and Scopus databases.\n\nBased on these 43 artic
 les\, a synthesis framework is being built that aims to systematize inform
 ation about the works found\, informing: 1) Source/Base/Collection\, 2) Re
 ference according to ABNT\, 3) Name of the Journal\, 4) Contact of the mai
 n author - email\, 5) Country of affiliation of the authors\, 6) Country o
 f the mapped community\, 7) Problem/Objective/Hypothesis\, 8) Methodology\
 , 9) Materials used\, 10) Techniques used\, 11) Main results\, 12) Does it
  work with Favela? 13) What is the nature of the community-based intervent
 ion? 14) Did favela residents operate the OpenStreetMap? 15) Where is the 
 favela and/or intervention? 16) If mapping in a favela\, what features and
  attributes were mapped? 17) Were integrated digital and analog cartograph
 ic technologies used? Which ones? 18) Were methods used for community appr
 opriation of cartographic tools and data? 19) Was educational material pro
 vided? Indicate link\, 19) Was a method for evaluating the tools and proce
 sses used implemented? 20) Were community impact indicators used? 21) Are 
 effective impacts felt by the community reported? Which ones?\n\nBy constr
 ucting this framework\, we are evaluating aspects such as the geographic d
 iversity in the use of OSM\, indicating the platform's flexibility and ada
 ptability\, or the still limited participation of local actors in mapping 
 their communities. By compiling data on the nature of community-based inte
 rventions\, techniques and methodologies used\, and community impact indic
 ators\, we aim to identify common patterns in the types of interventions t
 hat have been most effective. Furthermore\, the analysis of reported impac
 ts can indicate tangible benefits of these projects.\n\nThe analysis of ho
 w projects addressed training and education\, including the provision of e
 ducational materials and methods for community appropriation of cartograph
 ic tools and data\, can indicate strategies used to empower local communit
 ies. We are also analyzing the features and attributes mapped specifically
  in favelas\, to identify the main challenges and specific needs of these 
 areas\, supporting the indication of demands for improvements in methodolo
 gies and mapping tools in these urban contexts.\n\nThus\, we are building 
 a comprehensive framework on the current state of the use of OpenStreetMap
  for training and intervention in favelas\, identifying gaps\, challenges\
 , and opportunities for future research and projects.
DTSTAMP:20260514T065320Z
LOCATION:Room I
SUMMARY:OpenStreetMap in the Training of Local Actors in Projects Aimed at 
 Community-Based Interventions in Favelas: A Systematic Review Supported by
  AI - Patricia Lustosa Brito\, Pedro Melhado
URL:https://talks.staging.osgeo.org/foss4g-2024-academic-track/talk/HMEXFV/
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