Characterizing and Detecting Integrity Issues in OWL Instance Data
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The document discusses characterizing and detecting integrity issues in OWL instance data. It presents a method using autoepistemic description logics and SPARQL queries to efficiently evaluate instance data against ontologies in a closed world setting to identify logical inconsistencies and integrity issues that violate semantic expectations. The method creates ontologies with embedded expectations, acquires instance data, instantiates the ontologies, and publishes the data while checking for mismatches between the semantic expectations in the ontologies and observed data.
![Characterizing and Detecting Integrity Issues in OWL Instance Data Jiao Tao, Li Ding, Jie Bao, Deborah L. McGuinness ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],1. Create Ontologies (including embedded semantic expectations) Web O D 3. Instantiate Ontologies 4. Publish Instance Data O 2. Acquire Ontologies Do semantic expectations match between O and D? No Syntax Errors? Semantic expectation mismatches: (i) Logical inconsistencies (ii) Integrity issues](https://image.slidesharecdn.com/200810taodingbaomcguinnessowled-100701154800-phpapp01/85/characterizing-and-detecting-integrity-issues-in-owl-instance-data-1-320.jpg)
