Characterizing and Detecting Integrity Issues in OWL Instance Data

We view OWL instance data evaluation as a process in which instance data is checked for conformance with application requirements. We previously identified some integrity issues raised by applications demanding closed world reasoning. In this paper, we present a formal characterization of those integrity issues using autoepistemic operators, and a practical SPARQL-based issue checking approach that is a sound approximation for detecting integrity issues.

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The Inference Web is a Semantic Web based knowledge provenance infrastructure that supports interoperable explanations of sources, assumptions, learned information, and answers as an enabler for trust.

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