| dc.description.abstract | Data quality is crucial for operational efficiency
and sound decision making. This paper focuses on
believability, a major aspect of quality, measured
along three dimensions: trustworthiness,
reasonableness, and temporality. We ground our
approach on provenance, i.e. the origin and
subsequent processing history of data. We present our
provenance model and our approach for computing
believability based on provenance metadata. The
approach is structured into three increasingly complex
building blocks: (1) definition of metrics for assessing
the believability of data sources, (2) definition of
metrics for assessing the believability of data resulting
from one process run and (3) assessment of
believability based on all the sources and processing
history of data. We illustrate our approach with a
scenario based on Internet data. To our knowledge,
this is the first work to develop a precise approach to
measuring data believability and making explicit use of
provenance-based measurements. | en |
