Trust and Reputation Models for Quality Assessment of Human Sensor Observations

With the rise of human sensor observation as a major source of geospatial information, the traditional assessment of information quality based on parameters like accuracy, consistency and completeness is shifting to new measures. In volunteered geographic information (VGI) these conventional parameters are either lacking or not explicit. Regarding human observation quality as fitness for purpose, we propose to use trust and reputation as proxy measures of it. Trustworthy observations then take precedence over less trustworthy observations. Further, we propose that trust and reputation have spatial and temporal dimensions and we build computational models of trust for quality assessment including these dimensions. We present the case study of the

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2.0 VGI project for water quality management. Through agent based modeling, the study has established the validity of a spatio-temporal trust model for assessing the trustworthiness and hence the quality of human observations. We first introduce a temporally sensitive trust model and then discuss the extension of the temporal model with spatial dimensions and their effects on the computational trust model.