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CLASSIFICATION OF ERRORS IN GEOGRAPHIC DATA USING ISO 19157

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Autor(es):
Porfirio, Barbara K. A. ; Adaniya, Nicolle A. ; Josko, Joao M. B. ; Oikawa, Marcio K. ; IEEE
Número total de Autores: 5
Tipo de documento: Artigo Científico
Fonte: IGARSS 2020 - 2020 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM; v. N/A, p. 4-pg., 2020-01-01.
Resumo

The recent development of Geographic Information Systems and the high availability of geolocation devices have been stimulating significant growth in geographic data. The correct usage of geographic information is severely dependent on data quality and integration capacity. To find a suitable way to integrate geographic data, it is essential to define a strategy to identify as many errors as possible in that data. In this context, this project exploits the standard ISO 19157 and proposes a taxonomy which extends its main elements, focusing on the geographic data problems. The development of the taxonomy of geographic errors started by a survey of past contributions covering other taxonomies, errors, and data quality. This phase organized a set of frequent problems in geographic data. After that, the problems were classified considering the structure of standard ISO 19157. Taxonomy of errors can help users identify and solve problems on data, improving their integration and sharing potential. (AU)

Processo FAPESP: 15/01587-0 - Armazenagem, modelagem e análise de sistemas dinâmicos para aplicações em e-Science
Beneficiário:João Eduardo Ferreira
Modalidade de apoio: Auxílio à Pesquisa - Programa eScience e Data Science - Temático