Consistent View Mapping Of Large-scale Ontology Based On Inconsistency Check

In the field of Semantic Web, efficient query and utilization of large-scaleontology are very underlying and important problems. So far, the ontology datasets inSemantic Web are huge in size, while there is inevitable inconsistency contained inthese datasets. However, the users always need part of data of the huge dataset. Theextra huge dataset is inconvenient for usage, despite it contains the whole data. Inaddition, how to deal with the inconsistency is also an obstacle of Semantic Webdevelopment. So the current research focuses on the more convenient usage of datasetwhile dealing with the inconsistency.The aim of ontology modularization is to separate huge dataset into smaller ones.For the reason of the character of ontology structure, we should make sure theaccuracy and integrity during the process of modularization. The accuracy demandsthe precise split point, making the data not confused in non-relevant modular. Theintegrity demands the data from same structure located in the same modular.Besides, there are evitable conflict between data structure and definition ofconcepts, which bring negative impact for the dataset users. How to locate and dealwith the inconsistency is the core problem. Although there are many mechanisms toprocess ontology inconsistency, we adopt a version checking mechanism calledMORE and Pellet ontology Reasoner. Based on these, we create a solution to createconsistent ontology level by level.After the research and integrity of ontology modularization and consistencychecking, we design an ontology View Mapping with the technology of ontologyconsistency checking and ontology modularization. Despite we adopt others’technology, we make some improvement on it. Dividing original dataset into severalconsistent sub-ontologies, then combine some of them into View Mapping which cancover part of original ontology. This is a new kind of solution to use large inconsistentontology.