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Publication Additional Information
Publication Type
Journal Article
Authorship
Hojati Majid, Feick Rob, Roberts Steven, Farmer Carson, Robertson Colin
Title
Distributed spatial data sharing: a new model for data ownership and access control
Year
2023
Publication Outlet
Journal of Spatial Information Science No.27
DOI
https://doi.org/10.5311/JOSIS.2023.27.220
Citation
Hojati Majid, Feick Rob, Roberts Steven, Farmer Carson, Robertson Colin (2023) Distributed spatial data sharing: a new model for data ownership and access control, Journal of Spatial Information Science No.27
Abstract
With the advent of new technologies and broader participation in geospatial data production, new challenges emerge for spatial data sharing. Spatial data sharing practices are increasingly transacted through and, to varying degrees, controlled by a handful of privately controlled corporate services. Data production has evolved from being largely centralized, expert-oriented, and authoritative in nature to now also include hybrid data collection processes involving distributed assemblages of individuals who share and co-produce spatial data while interacting through centralized architectures and control regimes. These changes have resulted mainly from technological and social changes linked to the emergence of Web 2.0 and widely available Internet participation tools. Concerns about how spatial data access and sharing are controlled, particularly for sensitive or personally-identifying data, have increased interest in distributed file technologies that allow users to share resources independently of centralized platforms. This paper examines how spatial data sharing practices may move towards a more decentralized sharing ecosystem as technologies for a further distributed web mature. We identify this transition as increasingly hybridized forms of data ownership and access control concerns are coupled with new distributed systems (e.g., Web 3.0). We also discuss opportunities and barriers to distributed spatial data sharing, including possible benefits for big geographic data management and the need for protocols to share, integrate, and process spatial data shared on distributed networks.
Program Affiliations
GWF: Global Water Futures
Publication Stage
Published
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