| Abstract
|
As more applications are depending on sema … As more applications are depending on semantic web data from diverse sources, semantic web data evaluation is becoming more critical. While language validators and general reasoners can help, these typically focus on syntax and logical consistency. Many applications need additional support for finding possible issues (as well as provable mistakes). We are investigating methods and environments that provide computational support for identifying possible problems with instance data. We report on a line of work focusing on evaluation of provable and possible problems with OWL instance data and provide some discussion motivated by our first application setting validating large amounts of diverse explanation data. large amounts of diverse explanation data.
|
| Author
|
Li Ding +,
Jiao Tao +,
Deborah L. McGuinness +
|
| Bibtype
|
inproceedings +
|
| Booktitle
|
OWL Experiences and Directions DC (OWLED2008DC) +
|
| Key
|
DBLP:conf/owled/DingTM08 +
|
| Modification dateThis property is a special property in this wiki.
|
2 May 2009 11:27:56 +
|
| Paper
|
TW-2008-04.pdf +
|
| Paper url
|
http://www.webont.org/owled/2008dc/papers/owled2008dc_paper_25.pdf +
|
| Slides
|
TW-2008-04.ppt +
|
| Tag
|
Owl +,
Semantic web +,
Data evaluation +,
Computer science +
|
| Title
|
OWL Instance Data Evaluation +
|
| Tr id
|
TW-2008-04 +
|
| Year
|
2008 +
|
| Categories |
Statement of Interest,
Proceeding Paper,
Publication,
TW Technical Report
|
