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Erschienen in:
2009 | OriginalPaper | Buchkapitel
An Abstract Processing Model for the Quality of Context Data
verfasst von : Matthias Grossmann, Nicola Hönle, Carlos Lübbe, Harald Weinschrott
Erschienen in: Quality of Context
Verlag: Springer Berlin Heidelberg
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Data quality can be relevant to many applications. Especially applications coping with sensor data cannot take a single sensor value for granted. Because of technical and physical restrictions each sensor reading is associated with an uncertainty. To improve quality, an application can combine data values from different sensors or, more generally, data providers. But as different data providers may have diverse opinions about a certain real world phenomenon, another issue arises: inconsistency. When handling data from different data providers, the application needs to consider their trustworthiness. This naturally introduces a third aspect of quality: trust. In this paper we propose a novel processing model integrating the three aspects of quality: uncertainty, inconsistency and trust.