An approach for assessing the quality of crowdsourced geographic information in the flood management domain

Detalhes bibliográficos
Ano de defesa: 2019
Autor(a) principal: Degrossi, Livia Castro
Orientador(a): Não Informado pela instituição
Banca de defesa: Não Informado pela instituição
Tipo de documento: Tese
Tipo de acesso: Acesso aberto
Idioma: eng
Instituição de defesa: Biblioteca Digitais de Teses e Dissertações da USP
Programa de Pós-Graduação: Não Informado pela instituição
Departamento: Não Informado pela instituição
País: Não Informado pela instituição
Palavras-chave em Português:
Link de acesso: https://www.teses.usp.br/teses/disponiveis/55/55134/tde-06012020-174847/
Resumo: Crowdsourced Geographic Information (CGI) encompasses both active/conscious and passive/ unconscious georeferenced information generated by non-experts. The use of CGI in the domain of flood management is considerably recent and has been motivated by its potential as source of geographic information in situations where authoritative data is scarce or unavailable. Given that citizens may vary greatly in knowledge and expertise, the quality of such information is a key concern when making use of CGI. Moreover, the usability of the crowdsourcing platforms is another critical point that impacts the quality of CGI, since increasing complexity of such systems can lead to the provision of erroneous or inaccurate information. Although usability aspects have been increasingly discussed among designers and developers of computerized systems, there is a lack of studies that investigate strategies for the enhancement of the usability of crowdsourcing platforms. In this perspective, the assessment of CGI quality is an important step to determine if the information fits a specific purpose. A common way of assessing the quality of CGI gathered by crowdsourcing platforms is the evaluation of each CGI item. However, in crisis situations, there is short time to scrutinize a great amount of data and, therefore, minimizing information overload is critically important. An interesting, but poorly explored, strategy is the assessment of the quality of aggregated CGI elements, instead of a single one. This doctoral thesis proposes an approach for the improvement and assessment of CGI quality in the domain of flood management. It describes a taxonomy of methods for the assessment of CGI quality in the absence of authoritative data, as well as proposes a method for evaluating the quality of CGI and a new interface for the Citizen Observatory of Floods. Results obtained in the evaluation of the main contributions reveal that the method can explain the quality of CGI and the usability of the new interface increased.