Ontology Learning for the Semantic Web
IEEE Intelligent Systems
DAML+OIL: An Ontology Language for the Semantic Web
IEEE Intelligent Systems
Consistency Checking of Semantic Web Ontologies
ISWC '02 Proceedings of the First International Semantic Web Conference on The Semantic Web
Ontologies for Knowledge Management: An Information Systems Perspective
Knowledge and Information Systems
Human-centered ontology engineering: The HCOME methodology
Knowledge and Information Systems
Semantic Multimedia and Ontologies: Theory and Applications
Semantic Multimedia and Ontologies: Theory and Applications
Ontology Engineering --- The DOGMA Approach
Advances in Web Semantics I
Computability and Complexity Issues of Extended RDF
Proceedings of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence
Handbook on Ontologies
Content annotation for the semantic web: an automatic web-based approach
Knowledge and Information Systems
Cooperative ontology development environment CODE and a demo semantic web on economics
APWeb'05 Proceedings of the 7th Asia-Pacific web conference on Web Technologies Research and Development
On ontology-driven document clustering using core semantic features
Knowledge and Information Systems - Special Issue on "Context-Aware Data Mining (CADM)"
Knowledge and Information Systems
IKARUS-Onto: a methodology to develop fuzzy ontologies from crisp ones
Knowledge and Information Systems
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Whilst a variety of ontological engineering methodologies exist, their actual application is far from trivial, mainly due to the widely diverse nature of the steps involved, that require different forms of expertise, typically possessed by different individuals. In order to address this, in this work we propose the separation between the conceptualization and formalization parts of the process. As proof of concept we apply the proposed approach to the IKARUS methodology, develop a graphical tool to support the resulting methodology and present results from its experimental application. Early results show that the separation of the conceptualization and formalization parts of the ontological engineering methodologies can greatly facilitate the efficiency and effectiveness of the resulting methodologies.