Credibility is an important part of any quality scoring method. Scoring quality of a piece of information in regard to other messages gives an additional and crucial point of view. This quality dimension is especially useful when evaluating information produced by sensors. Often grouped in a network, a message from one sensor can be evaluated using other sources in this network which can highlight problematic messages leading to improved decision making or optimising maintenance operations. This paper considers the problem of defining credibility on sensor data: including definition of confirmation and invalidation for a piece of information in the case of the more challenging event-type messages. The proposed method aims to define a network of correlated sensors from which the relevant messages are extracted and then aggregated. Different propositions for the final aggregation step of confirming and invalidating messages leads to the definition of a flexible framework that can be adapted to different scenarios. An example is presented based on a real dataset that includes sensors from railway domain.
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