Jäger, MarkusKüng, Josef2016-12-292016-12-292017-01-04978-0-9981331-0-2http://hdl.handle.net/10125/41682In knowledge processing systems data is gathered from several sources. After some calculating and processing steps are taken in the system, a result is finally computed and may be used for further steps or by other systems. Most of the time the origin and provenance of input data is not verified. Using unverified data can cause inconsistencies in processing and generating output, and could lead to corrupting threats for the system and the environment as a whole. \ \ We propose an approach where several characterizing values in a given environment - trust of source, certainty of data, and importance (of data) in the current processing step - are used to compute new output characteristics of a knowledge processing system. These values represent the trustworthiness and the certainty of the output in multi-step processing systems based on all used sources and input data. We demonstrate the application of our approach on simple and advanced fictitious scenarios as well as on a real world scenario from the agricultural domain.10 pagesengAttribution-NonCommercial-NoDerivatives 4.0 InternationalCertaintyImportanceKnowledge Processing SystemsProvenanceTrustConference Paper10.24251/HICSS.2017.521