ue 12(2): e2

Research Article

Reduced Context Consistency Diagrams for Resolving Inconsistent Data

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  • @ARTICLE{10.4108/trans.ubienv.2012.10-12.e2,
        author={Viktoriya Degeler and Alexander Lazovik},
        title={Reduced Context Consistency Diagrams for Resolving Inconsistent Data},
        journal={EAI Endorsed Transactions on Ubiquitous Environments},
        keywords={Context-aware computing, context reasoning, context inconsistencies.},
  • Viktoriya Degeler
    Alexander Lazovik
    Year: 2012
    Reduced Context Consistency Diagrams for Resolving Inconsistent Data
    DOI: 10.4108/trans.ubienv.2012.10-12.e2
Viktoriya Degeler1,2,3, Alexander Lazovik1,2,3
  • 1: Distributed Systems Group,
  • 2: Johann Bernoulli Institute, University of Groningen,
  • 3: Nijenborgh 9, 9747 AG, The Netherlands


The ability of pervasive context-aware systems to perform efficiently relies on their ability to gather full and unambiguous information about the environment. But raw data collected from sensors is often noisy, imprecise and corrupted, which leads to inconsistencies and conflicts in gathered data. Also environment is only partially observable, thus allowing ambiguities in the knowledge about its state. In the paper we present reduced context consistency diagrams (RCCD), data structures that allow to store the information about the environment even with the presence of inconsistencies, conflicts, and ambiguities. We provide a mechanism for reasoning about the current situation using these diagrams, and show how to obtain information about the most probable situation at each moment of time. The case study shows the 50% reduction in incorrect sensor readings. The evaluation shows RCCD to be applicable to real-time context inference problems.