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dc.contributor.authorTao, Jiao
dc.contributor.authorDing, Li
dc.contributor.authorBao, Jie
dc.contributor.authorMcGuinness, Deborah
dc.description.abstractWe 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.
dc.subjectInference Web
dc.titleCharacterizing and Detecting Integrity Issues in OWL Instance Data

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