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A context sensitive approach to anonymizing public participation GIS data: From development to the assessment of anonymization effects on data quality / Kamyar Hasanzadeh in Computers, Environment and Urban Systems, vol 83 (September 2020)  

Public [article]  inComputers, Environment and Urban Systems > vol 83 (September 2020) . - n° 101513 Titre : A context sensitive approach to anonymizing public participation GIS data: From development to the assessment of anonymization effects on data quality Type de document : Article/Communication Auteurs : Kamyar Hasanzadeh, Auteur ; Anna Kajosaari, Auteur ; Dan Häggman, Auteur ; Marketta Kyttä, Auteur Année de publication : 2020 Article en page(s) : n° 101513 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Systèmes d'information géographique [Termes IGN] analyse spatiale [Termes IGN] anonymisation [Termes IGN] approche participative [Termes IGN] collecte de données [Termes IGN] données ouvertes [Termes IGN] protection de la vie privée [Termes IGN] qualité des données [Termes IGN] SIG participatif [Termes IGN] système d'information géographique Résumé : (auteur) Use of Public Participation Geographic Information System (PPGIS) for data collection has been significantly growing over the past few years in different areas of research and practice. With the growing amount of data, there is little doubt that a potentially wider community can benefit from open access to them. Additionally, open data add to the transparency of research and can be considered as an essential feature of science. However, data anonymization is a complex task and the unique characteristics of PPGIS add to this complexity. PPGIS data often include personal spatial and non-spatial information, which essentially require different approaches for anonymization. In this study, we first identify different privacy concerns and then develop a PPGIS data anonymization strategy to overcome them for an open PPGIS data. Specifically, this article introduces a context-sensitive spatial anonymization method to protect individual home locations while maintaining their spatial resolution for mapping purposes. Furthermore, this study empirically evaluates the effects of data anonymization on PPGIS data quality. The results indicate that a satisfactory level of anonymization can be reached using this approach. Moreover, the assessment results indicate that the environmental and home range measurements as well as their intercorrelations are not significantly biased by the anonymization. However, necessary analytical measures such as use of larger spatial units is recommendable when anonymized data is used. In this study, European data protection regulations were used as the legal guidelines. However, adaptation of methods employed in this study may be also relevant to other countries where comparable regulations exist. Although specifically targeted at PPGIS data, what is discussed in this paper can be applicable to other similar spatial datasets as well. Numéro de notice : A2020-698 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1016/j.compenvurbsys.2020.101513 Date de publication en ligne : 04/07/2020 En ligne : https://doi.org/10.1016/j.compenvurbsys.2020.101513 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96252 [article]