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A taxonomy of quality assessment methods for volunteered and crowdsourced geographic information

The growing use of crowdsourced geographic information (CGI) has prompted the employment of several methods for assessing information quality, which are aimed at addressing concerns on the lack of quality of the information provided by non‐experts. In this work, we propose a taxonomy of methods for...

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Autores principales: Degrossi, Lívia Castro, Porto de Albuquerque, João, dos Santos Rocha, Roberto, Zipf, Alexander
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5993263/
https://www.ncbi.nlm.nih.gov/pubmed/29937686
http://dx.doi.org/10.1111/tgis.12329
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author Degrossi, Lívia Castro
Porto de Albuquerque, João
dos Santos Rocha, Roberto
Zipf, Alexander
author_facet Degrossi, Lívia Castro
Porto de Albuquerque, João
dos Santos Rocha, Roberto
Zipf, Alexander
author_sort Degrossi, Lívia Castro
collection PubMed
description The growing use of crowdsourced geographic information (CGI) has prompted the employment of several methods for assessing information quality, which are aimed at addressing concerns on the lack of quality of the information provided by non‐experts. In this work, we propose a taxonomy of methods for assessing the quality of CGI when no reference data are available, which is likely to be the most common situation in practice. Our taxonomy includes 11 quality assessment methods that were identified by means of a systematic literature review. These methods are described in detail, including their main characteristics and limitations. This taxonomy not only provides a systematic and comprehensive account of the existing set of methods for CGI quality assessment, but also enables researchers working on the quality of CGI in various sources (e.g., social media, crowd sensing, collaborative mapping) to learn from each other, thus opening up avenues for future work that combines and extends existing methods into new application areas and domains.
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spelling pubmed-59932632018-06-20 A taxonomy of quality assessment methods for volunteered and crowdsourced geographic information Degrossi, Lívia Castro Porto de Albuquerque, João dos Santos Rocha, Roberto Zipf, Alexander Trans GIS Research Articles The growing use of crowdsourced geographic information (CGI) has prompted the employment of several methods for assessing information quality, which are aimed at addressing concerns on the lack of quality of the information provided by non‐experts. In this work, we propose a taxonomy of methods for assessing the quality of CGI when no reference data are available, which is likely to be the most common situation in practice. Our taxonomy includes 11 quality assessment methods that were identified by means of a systematic literature review. These methods are described in detail, including their main characteristics and limitations. This taxonomy not only provides a systematic and comprehensive account of the existing set of methods for CGI quality assessment, but also enables researchers working on the quality of CGI in various sources (e.g., social media, crowd sensing, collaborative mapping) to learn from each other, thus opening up avenues for future work that combines and extends existing methods into new application areas and domains. John Wiley and Sons Inc. 2018-04-19 2018-04 /pmc/articles/PMC5993263/ /pubmed/29937686 http://dx.doi.org/10.1111/tgis.12329 Text en © 2018 The Authors. Transactions in GIS published by John Wiley & Sons Ltd. This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Articles
Degrossi, Lívia Castro
Porto de Albuquerque, João
dos Santos Rocha, Roberto
Zipf, Alexander
A taxonomy of quality assessment methods for volunteered and crowdsourced geographic information
title A taxonomy of quality assessment methods for volunteered and crowdsourced geographic information
title_full A taxonomy of quality assessment methods for volunteered and crowdsourced geographic information
title_fullStr A taxonomy of quality assessment methods for volunteered and crowdsourced geographic information
title_full_unstemmed A taxonomy of quality assessment methods for volunteered and crowdsourced geographic information
title_short A taxonomy of quality assessment methods for volunteered and crowdsourced geographic information
title_sort taxonomy of quality assessment methods for volunteered and crowdsourced geographic information
topic Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5993263/
https://www.ncbi.nlm.nih.gov/pubmed/29937686
http://dx.doi.org/10.1111/tgis.12329
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