Trustworthiness Modelling on Continuous Environmental Measurement

Mats Neovius, Markus Stocker, Mauno Rönkkö, Luigia Petre

    Research output: Chapter in Book/Conference proceedingConference contributionScientificpeer-review

    1 Citation (Scopus)


    In the domain of environmental sciences, measurement is the process that maps some observed phenomenon to a formal measurement value, the latter being the result of a measurement process. The measurement process relies on data representing physical quantities of possibly continuously changing phenomena. Because of the inherent imprecision of this source data and interpretations made within the measurement process itself, the measurement processes and their measurement values are plagued with quality issues. Many of these quality issues may be parameterised and provided as metadata of the measurement value, e.g. precision, resolution, trustworthiness. Of these, the trustworthiness quality parameter is evaluated by the consumer of the measurement value; this evaluation is a subjective perception of the level of momentary reliance justifiably placed on the measurement value and possible quality parameters. Initially the level of trustworthiness is thus vacuous with the consumer’s trustworthiness building up by gained evidence in the provider in providing this type of a measurement value. In this paper we define a method for representing, calculating and monitoring the trustworthiness parameter placed on a provider providing measurement values. The inherent imprecision of any measurement value is considered as a level of (un)certainty with a three-valued representation. The presented method is based on Dempster-Shafer theory of evidence and uses Subjective Logic to calculate with the trustworthiness. We apply techniques of reputation based trustworthiness for a meaningful reliability analysis in environmental sciences. We validate our method on data from the indoor environment of a residential house.
    Original languageUndefined/Unknown
    Title of host publicationProceedings of the 7th International Congress on Environmental Modelling and Software (iEMSs)
    Editors Ames, D.P., Quinn, N.W.T., Rizzoli, A.E.
    PublisherInternational congress on environmental modelling and software
    ISBN (Print)978-88-9035-744-2
    Publication statusPublished - 2014
    MoE publication typeA4 Article in a conference publication
    Eventconference; 2014-06-15; 2014-06-19 - Åbo Akademi University
    Duration: 15 Jun 201419 Jun 2014


    Conferenceconference; 2014-06-15; 2014-06-19


    • evidence
    • sensor data
    • trustworthiness
    • uncertainty

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