Show simple item record

dc.contributor.authorTao, Jiao
dc.contributor.authorDing, Li
dc.contributor.authorBao, Jie
dc.contributor.authorMcGuinness, Deborah
dc.date.accessioned2022-02-18T02:39:25Z
dc.date.available2022-02-18T02:39:25Z
dc.date.issued2008-10-26
dc.identifier.other278
dc.identifier.urihttp://archive.tw.rpi.edu/media/latest/Characterizing_and_Detecting_Integrity_Issues_in_OWL_Instance_Data.pdf
dc.identifier.urihttps://hdl.handle.net/20.500.13015/4680
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.relation.urihttps://tw.rpi.edu/project/InferenceWeb
dc.subjectInference Web
dc.titleCharacterizing and Detecting Integrity Issues in OWL Instance Data


Files in this item

FilesSizeFormatView

There are no files associated with this item.

This item appears in the following Collection(s)

Show simple item record