This paper investigates the causes of imprecision of the observations and uncertainty of the authors who create Volunteer Geographic Information (VGI), i.e., georeferenced contents generated by volunteers when participating in some citizen science project. Specifically, various aspects of imprecision and uncertainty of VGI are outlined and, to cope with them, a knowledge-based approach is suggested based on the creation and management of "contextualized VGI". A case study example in agriculture is reported where contextualized VGI can be created about in situ crops observations by the use of a smart app that supports volunteers by means of both an ontology and the representation of the context of the geo-localization. Furthermore, an approach to cope with both ill-defined knowledge and volunteer's uncertainty or imprecise observations is defined based on a fuzzy ontology with uncertainty level-based approximate reasoning. By representing uncertainty and imprecision of VGI, users, i.e., consumers, can exploit quality checking mechanisms to filter VGI based on their needs.

"Contextualized VGI" Creation and Management to Cope with Uncertainty and Imprecision

Gloria Bordogna;Luca Frigerio;Pietro Alessandro Brivio;Giacinto Manfron;Simone Sterlacchini
2016

Abstract

This paper investigates the causes of imprecision of the observations and uncertainty of the authors who create Volunteer Geographic Information (VGI), i.e., georeferenced contents generated by volunteers when participating in some citizen science project. Specifically, various aspects of imprecision and uncertainty of VGI are outlined and, to cope with them, a knowledge-based approach is suggested based on the creation and management of "contextualized VGI". A case study example in agriculture is reported where contextualized VGI can be created about in situ crops observations by the use of a smart app that supports volunteers by means of both an ontology and the representation of the context of the geo-localization. Furthermore, an approach to cope with both ill-defined knowledge and volunteer's uncertainty or imprecise observations is defined based on a fuzzy ontology with uncertainty level-based approximate reasoning. By representing uncertainty and imprecision of VGI, users, i.e., consumers, can exploit quality checking mechanisms to filter VGI based on their needs.
2016
Istituto per la Dinamica dei Processi Ambientali - IDPA - Sede Venezia
Istituto di Geologia Ambientale e Geoingegneria - IGAG
Istituto per il Rilevamento Elettromagnetico dell'Ambiente - IREA
contextualized Volunteered Geographic Information (VGI);
smart app
uncertainty
Imprecision
fuzzy ontology
level-based approximate reasoning
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/328975
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