Characterizing and detecting integrity issues in owl instance data

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Reference:

1. Jiao Tao, Li Ding, Jie Bao, Deborah L. McGuinness. Characterizing and Detecting Integrity Issues in OWL Instance Data , Proceedings of the fifth International Workshop on The OWL: Experiences and Direction (OWLED), 2008

bibtex

@inproceedings { TW-2008-22 ,
  author = "Jiao Tao, Li Ding, Jie Bao, Deborah L. McGuinness", 
booktitle = "Proceedings of the fifth International Workshop on The OWL: Experiences and Direction (OWLED)", 
title = "Characterizing and Detecting Integrity Issues in OWL Instance Data", 
year = "2008", 
} 

abstract: 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.

download:

• paper: TW-2008-22.pdf (http://www.webont.org/owled/2008/papers/owled2008eu_submission_8.pdf)
• slides: TW-2008-22.ppt