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Assessing crowdsourced POI quality: combining methods based on reference data, history, and spatial relations / Guillaume Touya in ISPRS International journal of geo-information, vol 6 n° 3 (March 2017)  

Public [article]  inISPRS International journal of geo-information > vol 6 n° 3 (March 2017) . - pp 1 - 29 Titre : Assessing crowdsourced POI quality: combining methods based on reference data, history, and spatial relations Type de document : Article/Communication Auteurs : Guillaume Touya , Auteur ; Vyron Antoniou, Auteur ; Ana-Maria Olteanu-Raimond , Auteur ; Marie-Dominique Van Damme , Auteur Année de publication : 2017 Projets : ENERGIC / Capineri, Cristina Article en page(s) : pp 1 - 29 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées [Termes IGN] analyse multicritère [Termes IGN] changement temporel [Termes IGN] données localisées des bénévoles [Termes IGN] évaluation des données [Termes IGN] OpenStreetMap [Termes IGN] point d'intérêt [Termes IGN] production participative [Termes IGN] qualité des données Résumé : (Auteur) With the development of location-aware devices and the success and high use of Web 2.0 techniques, citizens are able to act as sensors by contributing geographic information. In this context, data quality is an important aspect that should be taken into account when using this source of data for different purposes. The goal of the paper is to analyze the quality of crowdsourced data and to study its evolution over time. We propose two types of approaches: (1) use the intrinsic characteristics of the crowdsourced datasets; or (2) evaluate crowdsourced Points of Interest (POIs) using external datasets (i.e., authoritative reference or other crowdsourced datasets), and two different methods for each approach. The potential of the combination of these approaches is then demonstrated, to overcome the limitations associated with each individual method. In this paper, we focus on POIs and places coming from the very successful crowdsourcing project: OpenStreetMap. The results show that the proposed approaches are complementary in assessing data quality. The positive results obtained for data matching show that the analysis of data quality through automatic data matching is possible but considerable effort and attention are needed for schema matching given the heterogeneity of OSM and the representation of authoritative datasets. For the features studied, it can be noted that change over time is sometimes due to disagreements between contributors, but in most cases the change improves the quality of the data. Numéro de notice : A2017-188 Affiliation des auteurs : LASTIG COGIT+Ext (2012-2019) Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi6030080 Date de publication en ligne : 14/03/2017 En ligne : http://dx.doi.org/10.3390/ijgi6030080 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=84796 [article]