  Data quality and data cleaning are context dependent activities. Starting
from this observation, in previous work a context model for the assessment of
the quality of a database instance was proposed. In that framework, the context
takes the form of a possibly virtual database or data integration system into
which a database instance under quality assessment is mapped, for additional
analysis and processing, enabling quality assessment. In this work we extend
contexts with dimensions, and by doing so, we make possible a multidimensional
assessment of data quality assessment. Multidimensional contexts are
represented as ontologies written in Datalog+-. We use this language for
representing dimensional constraints, and dimensional rules, and also for doing
query answering based on dimensional navigation, which becomes an important
auxiliary activity in the assessment of data. We show ideas and mechanisms by
means of examples.
