Supporting ontological analysis of taxonomic relationships
Data & Knowledge Engineering - ER2000
A semiotic metrics suite for assessing the quality of ontologies
Data & Knowledge Engineering - Special issue: Natural language and database and information systems: NLDB 03
Natural Language-Based Approach for Helping in the Reuse of Ontology Design Patterns
EKAW '08 Proceedings of the 16th international conference on Knowledge Engineering: Practice and Patterns
Experiments on pattern-based ontology design
Proceedings of the fifth international conference on Knowledge capture
Modelling ontology evaluation and validation
ESWC'06 Proceedings of the 3rd European conference on The Semantic Web: research and applications
ONTO-EVOAL an ontology evolution approach guided by pattern modeling and quality evaluation
FoIKS'10 Proceedings of the 6th international conference on Foundations of Information and Knowledge Systems
A survey on ontologies for human behavior recognition
ACM Computing Surveys (CSUR)
| Hi-index | 0.00 |
Ontology quality can be affected by the difficulties involved in ontology modelling which may imply the appearance of anomalies in ontologies. This situation leads to the need of validating ontologies, that is, assessing their quality and correctness. Ontology validation is a key activity in different ontology engineering scenarios such as development and selection. This paper contributes to the ontology validation activity by proposing a web-based tool, called OOPS!, independent of any ontology development environment, for detecting anomalies in ontologies. This tool will help developers to improve ontology quality by automatically detecting potential errors.