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| Characterizing and detecting integrity issues in owl instance data |
| Abstract | We view OWL instance data evaluation as a … 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. roximation for detecting integrity issues. |
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| Address | Karlsruhe, Germany + |
| Author | Jiao Tao +, Li Ding +, Jie Bao +, Deborah L. McGuinness + |
| Bibtype | inproceedings + |
| Booktitle | Proceedings of the fifth International Workshop on The OWL: Experiences and Direction (OWLED) + |
| Key | TW-2008-22 + |
| Modification dateThis property is a special property in this wiki. | 2 May 2009 04:23:29 + |
| Month | October + |
| Paper | TW-2008-22.pdf + |
| Paper url | http://www.webont.org/owled/2008/papers/owled2008eu_submission_8.pdf + |
| Relation | OWL Instance-data Evaluation (Project) + |
| Slides | TW-2008-22.ppt + |
| Tag | Computer science + |
| Title | Characterizing and Detecting Integrity Issues in OWL Instance Data + |
| Tr id | TW-2008-22 + |
| Year | 2008 + |
| Categories | Workshop Paper, Proceeding Paper, Publication, TW Technical Report |
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