Abstract
Over the past several years, volunteered geographic information (VGI) has expanded rapidly. VGI collection has been proven to serve as a highly successful means of acquiring timely and detailed global spatial data. However, VGI includes several special properties. For example, the contributor’s reputation affects the quality of objects edited, and a geographic object may have multiple versions. The existing spatio-temporal data model cannot describe the unique properties of VGI. Therefore, a spatio-temporal VGI model considering trust-related information is presented in this paper. In this model, central elements of the VGI environment, e.g., geographic entity, entity state, state version, contributor, reputation, geographic event, and edit event, and their interaction mechanisms are analysed. Major VGI objects and relations are determined using the object-oriented method and trust-related operations, and their relationships are analysed, and nine linkage rules among trust-related operations are found to maintain the consistency of corresponding data. A prototype system for the spatio-temporal VGI model is presented, and the effectiveness of the model is verified.
Highlights
Crowdsourcing data, i.e., volunteered geographic information (VGI) [1,2,3], constitute a promising tool for borderland data acquisition [4]
VGI is becoming increasingly important as an alternative source of spatial data [4]
Uncertainties in terms of its quality have limited its use in GIS-related applications [12]
Summary
Crowdsourcing data, i.e., volunteered geographic information (VGI) [1,2,3], constitute a promising tool for borderland data acquisition [4]. Several researchers have focused on the overall quality evaluation of VGI datasets, e.g., data completeness, positional accuracy, etc., by comparing crowdsourcing data with authoritative data [12] Such methods cannot be used to assess the quality of single features in a VGI database [13]. In a VGI system, trust-related information, i.e., version, state, version trust, contributor reputation, etc., must be determined. Based on the above observations, a spatio-temporal VGI model considering trust-related information is presented in this paper. In this model, geographic objects, object states, and state versions are used as three different element levels.
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