Authors:
Muhammad Fahad
1
;
Muhammad Abdul Qadir
1
and
Muhammad Wajahat Noshairwan
2
Affiliations:
1
Center for Distributed and Semantic Computing, M.A.J.U, Pakistan
;
2
National Engineerning and Sceintific Comission, Pakistan
Keyword(s):
Ontological Errors Taxonomy, Ontology Evaluation, Ontology Validation and Verification, Ontology Design Anomalies, Ontology Merging, Ontology Mapping, Semantic Web.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Data Engineering
;
Enterprise Information Systems
;
Information Systems Analysis and Specification
;
Knowledge Engineering and Ontology Development
;
Knowledge-Based Systems
;
Ontologies and the Semantic Web
;
Ontology Engineering
;
Symbolic Systems
Abstract:
Mapping and merging of multiple ontologies to produce consistent, coherent and correct merged global ontology is an essential process to enable heterogeneous multi-vendors semantic-based systems to communicate with each other. To generate such a global ontology automatically, the individual ontologies must be free of (all types of) errors. We have observed that the present error classification does not include all the errors. This paper extends the existing error classification (Inconsistency, Incompleteness and Redundancy) and provides a discussion about the consequences of these errors. We highlight the problems that we faced while developing our DKP-OM, ontology merging system and explain how these errors became obstacles in efficient ontology merging process. It integrates the ontological errors and design anomalies for content evaluation of ontologies under one framework. This framework helps ontologists to build semantically correct ontology free from errors that enables effect
ive and automatic ontology mapping and merging with lesser user intervention.
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