Assuring the quality of volunteered geographic information

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Crowdsourcing for climate and atmospheric sciences: current status and future potential (2015, positive): “Furthermore the geographical context associated with contributions may be used to check the reasonableness of the data provided by a source given existing knowledge (Goodchild and Li, 2012).”
Data-driven geography (2014, positive): “Goodchild and Li (2012) discuss this approach in the context of crowdsourced geographic information.”
Mapping the Data Shadows of Hurricane Sandy: Uncovering the Sociospatial Dimensions of ‘Big Data’ (2014, background): “…et al. (2012) employ a networked or topological understanding of sociospatial relations by focusing on social connections between Twitter users, while work by Goodchild and Li (2012); Haklay (2010) focused on questions about the quality and locational accuracy of volunteered geographic information.”
Crowdsourcing, Citizen Science or Volunteered Geographic Information? The Current State of Crowdsourced Geographic Information (2016, background): “Fortunately, a variety of broad approaches for quality assessment and control exist [70], although further work is required if the full potential of citizen-derived data is to be achieved.”
A review of volunteered geographic information quality assessment methods (2017, methodology): “Based on such characteristics, Goodchild and Li (2012) propose three approaches to ensure the quality of VGI: 1. crowd-sourced, 2. social, and 3. geographic.”