%0 Conference Proceedings
%4 sid.inpe.br/mtc-m16c/2020/12.14.10.58
%2 sid.inpe.br/mtc-m16c/2020/12.14.10.58.16
%@issn 2179-4847
%T QualiOSM: Improving Data Quality in the Collaborative Mapping Tool OpenStreetMap
%D 2020
%A Medeiros, Gabriel F. B. de,
%A Degrossi, Lívia C.,
%A Holanda, Maristela,
%@affiliation Universidade de Brasília (UnB)
%@affiliation Fundação Getúlio Vargas (FGV)
%@affiliation Universidade de Brasília (UnB)
%@electronicmailaddress gabriel.medeiros93@gmail.com
%@electronicmailaddress liviadegrossi@gmail.com
%@electronicmailaddress mholanda@unb.br
%E Carneiro, Tiago Garcia de Senna (UFOP),
%E Felgueiras, Carlos Alberto (INPE),
%B Simpósio Brasileiro de Geoinformática, 21 (GEOINFO)
%C On-line
%8 30 nov. a 03 dez. 2020
%I Instituto Nacional de Pesquisas Espaciais (INPE)
%J São José dos Campos
%P 10-21
%S Anais
%X The collaborative mapping tool OpenStreetMap (OSM) has a large database in which thousands of users are able to insert, edit and delete geo- graphic data from the Earths surface. As evidenced in multiple studies, col- laborative tools tend to have a lack of data quality, since the information is often provided by inexperienced users. Due to its complexity, the quality of ge- ographic data can be measured based on different aspects, which have been called quality dimensions in literature. In this context, this paper proposes the implementation of the QualiOSM tool in order to improve the quality dimension of attribute completeness within OpenStreetMap platform, increasing the ad- dress information associated with objects. The tool was tested in two different scenarios in Brazil: the city center of Brasilia, capital of the country, and part of the city of Rio Branco, in the state of Acre.
%9 Sistemas de Informação Geográfica (SIG)
%@language en
%3 p2.pdf