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                    Section 1: Publication
                                
                Publication Type
                Journal Article
                                
                Authorship
                Hojati, M., Farmer, C., Feick, R., & Robertson, C. 
                                
                Title
                Decentralized geoprivacy: leveraging social trust on the distributed web
                                
                Year
                2021
                                
                Publication Outlet
                International Journal of Geographic Information Science
                                
                DOI
                
                                
                ISBN
                
                                
                ISSN
                
                                
                Citation
                
                    Hojati, M., Farmer, C., Feick, R., & Robertson, C. (2021). Decentralized geoprivacy: leveraging social trust on the distributed web. International Journal of Geographic Information Science. In Press. 
https://doi.org/10.1080/13658816.2021.1931236.
                
 
                                
                Abstract
                
                    Despite several high-profile data breaches and business models that commercialize user data, participation in social media networks continues to require users to trust corporations to safeguard their personal data. Since these data increasingly contain geographic references that allude to individuals’ locations and movements, the need for new approaches to geoprivacy and data sovereignty has grown. We develop a geoprivacy framework that couples two emerging technologies – decentralized data storage and discrete global grid systems – to facilitate fine-grained user control over the ownership of, access to and map-based representation of their data. The framework is illustrated with a dynamic k-anonymity model that links the geographic precision of shared data to social trust within in a social network. In this framework, users’ spatio-temporal data are shared through a decentralized system and are represented on a discrete global grid data model at spatial resolutions that correspond to varying degrees of trust between individuals who are exchanging information. Our framework has several advantages over centralized geoprivacy approaches, namely trust in a third-party entity is not required and geoprivacy is dynamic and context-dependent with users maintaining autonomy. As the distributed web begins to emerge, so too can the next generation of geographic information sharing tools.
                
                                
                Plain Language Summary