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A cross-analysis framework for multi-source volunteered, crowdsourced, and authoritative geographic information : The case study of volunteered personal traces analysis against transport network data / Gloria Bordogna in Geo-spatial Information Science, vol 21 n° 3 (October 2018)  

Public [article]  inGeo-spatial Information Science > vol 21 n° 3 (October 2018) . - pp 257 - 271 Titre : A cross-analysis framework for multi-source volunteered, crowdsourced, and authoritative geographic information : The case study of volunteered personal traces analysis against transport network data Type de document : Article/Communication Auteurs : Gloria Bordogna, Auteur ; Steven Capelli, Auteur ; Daniele E. Ciriello, Auteur ; Guiseppe Psaila, Auteur Année de publication : 2018 Article en page(s) : pp 257 - 271 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] Bergame [Termes IGN] cadre conceptuel [Termes IGN] données hétérogènes [Termes IGN] données localisées de référence [Termes IGN] données localisées des bénévoles [Termes IGN] format JSON [Termes IGN] mobilité urbaine [Termes IGN] requête spatiale [Termes IGN] réseau de transport [Termes IGN] segmentation sémantique [Termes IGN] trace numérique Résumé : (Auteur) The paper discusses the need of a high-level query language to allow analysts, geographers and, in general, non-programmers to easily cross-analyze multi-source VGI created by means of apps, crowd-sourced data from social networks and authoritative geo-referenced data, usually represented as JSON data sets (nowadays, the de facto standard for data exported by social networks). Since an easy to use high-level language for querying and manipulating collections of possibly geo-tagged JSON objects is still unavailable, we propose a truly declarative language, named J-CO-QL, that is based on a well-defined execution model. A plug-in for a GIS permits to visualize geo-tagged data sets stored in a NoSQL database such as MongoDB; furthermore, the same plug-in can be used to write and execute J-CO-QL queries on those databases. The paper introduces the language by exemplifying its operators within a real study case, the aim of which is to understand the mobility of people in the neighborhood of Bergamo city. Cross-analysis of data about transportation networks and VGI from travelers is performed, by means of J-CO-QL language, capable to manipulate and transform, combine and join possibly geo-tagged JSON objects, in order to produce new possibly geo-tagged JSON objects satisfying users’ needs. Numéro de notice : A2018-646 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10095020.2017.1374703 Date de publication en ligne : 21/09/2018 En ligne : https://doi.org/10.1080/10095020.2017.1374703 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93316 [article]