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Crowdsourcing without data bias: Building a quality assurance system for air pollution symptom mapping / Marta Samulowska in ISPRS International journal of geo-information, vol 10 n° 2 (February 2021)  

Public [article]  inISPRS International journal of geo-information > vol 10 n° 2 (February 2021) . - n° 46 Titre : Crowdsourcing without data bias: Building a quality assurance system for air pollution symptom mapping Type de document : Article/Communication Auteurs : Marta Samulowska, Auteur ; Szymon Chmielewski, Auteur ; Edwin Raczko, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 46 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web [Termes IGN] assurance qualité [Termes IGN] carte sanitaire [Termes IGN] données localisées des bénévoles [Termes IGN] erreur systématique [Termes IGN] pollution atmosphérique [Termes IGN] production participative [Termes IGN] qualité de l'air [Termes IGN] qualité des données [Termes IGN] science citoyenne [Termes IGN] surveillance sanitaire [Termes IGN] zone urbaine Résumé : (auteur) Crowdsourcing is one of the spatial data sources, but due to its unstructured form, the quality of noisy crowd judgments is a challenge. In this study, we address the problem of detecting and removing crowdsourced data bias as a prerequisite for better-quality open-data output. This study aims to find the most robust data quality assurance system (QAs). To achieve this goal, we design logic-based QAs variants and test them on the air quality crowdsourcing database. By extending the paradigm of urban air pollution monitoring from particulate matter concentration levels to air-quality-related health symptom load, the study also builds a new perspective for citizen science (CS) air quality monitoring. The method includes the geospatial web (GeoWeb) platform as well as a QAs based on conditional statements. A four-month crowdsourcing campaign resulted in 1823 outdoor reports, with a rejection rate of up to 28%, depending on the applied. The focus of this study was not on digital sensors’ validation but on eliminating logically inconsistent surveys and technologically incorrect objects. As the QAs effectiveness may depend on the location and society structure, that opens up new cross-border opportunities for replication of the research in other geographical conditions. Numéro de notice : A2021-153 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi10020046 Date de publication en ligne : 22/01/2021 En ligne : https://doi.org/10.3390/ijgi10020046 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97064 [article]