Models of direct editing of government spatial data: challenges and constraints to the acceptance of contributed data

Abstract

The current popularity of government open data platforms as a way to share geospatial data has created an opportunity for government to receive direct feedback and edits on this very same data. This research proposes four models that can define how government accepts direct edits and feedback on geospatial data. The four models are a “status quo” of open data provision, data curation, data mirroring, and crowdsourcing. These models are placed on a continuum of government control ranging from high levels of control over data creation to a low level of control. Each model is discussed, with relevant challenges highlighted. These four models present an initial suite of options for governments looking to accept direct edits from data end users and can be framed as a partial realization of many of the principles of open government. Despite the varied potential of these approaches, they generate a shift in locus of control away from government, creating several areas of risk for government. Of these models, near-term interest may focus on data curation and data mirroring as evolutionary, rather than revolutionary steps that expand on the simple provision of open data.