Goodchild does a thorough job assessing the benefits and hindrances of his three methods for quality assurance of VGI. His first two, the crowd-sourcing approach and the social approach, he evaluates in comparison to Wikipedia contribution. Goodchild failed to specify a few important details of the social approach. Ideally Wikipedia contributions are made by users who have specific knowledge of a subject. User profiles on Wikipedia list a user’s contributions/edits, as well as an optional description of the user’s background and interests (and accolades if they are a frequent or well-regarded contributor). An OSM user profile could similarly denote their [physical] area of expertise, and also register regions where the user has made the most contributions/edits, giving them more “credibility” for other related contributions.
An important aspect that Goodchild failed to mention regarding the crowd-sourcing approach is the barrier to editing OSM features. While Linus’ Law can certainly apply for geographic data, someone who sees an error in OSM would need to be a registered and knowledgeable user to fix the error. In Wikipedia, an “Edit” button is constantly visible and one need not register to make an edit. Legitimate Wikipedia contributions must also be accompanied by a citation of an outside source, an important facet that geographic information often lacks.
The geographic approach to VGI quality assurance requires a set of “rules.” Goodchild is concerned with the ability of these rules to distinguish between a real and imagined landscape, giving an example based on the characteristics of physical features such as coastlines, river systems, and settlement location. Satellite imagery has provided the basis of much of OSM’s physical geographic features. Quality assurance is more often concerned with the name and location of man-made features. A set of rules for man-made features could be more easily determined through a large-scale analysis of similarly tagged features and their relationship to their surroundings. I.e. a restaurant located in a park away from a street might be flagged as “suspicious” since its surroundings do not match the surroundings of other “restaurant” features.