CREAM: creating relational metadata with a component-based, ontology-driven annotation framework
Proceedings of the 1st international conference on Knowledge capture
Knowledge Processes and Ontologies
IEEE Intelligent Systems
MnM: Ontology Driven Semi-automatic and Automatic Support for Semantic Markup
EKAW '02 Proceedings of the 13th International Conference on Knowledge Engineering and Knowledge Management. Ontologies and the Semantic Web
Selected Papers from the Symposium on Conceptual Modeling, Current Issues and Future Directions
Reasoning with Expressive Description Logics: Theory and Practice
CADE-18 Proceedings of the 18th International Conference on Automated Deduction
Meteor-s web service annotation framework
Proceedings of the 13th international conference on World Wide Web
KIM – a semantic platform for information extraction and retrieval
Natural Language Engineering
Introduction to the special issue on semantic integration
ACM SIGMOD Record
SAWSDL: Semantic Annotations for WSDL and XML Schema
IEEE Internet Computing
Goal annotation of process models for semantic enrichment of process knowledge
CAiSE'07 Proceedings of the 19th international conference on Advanced information systems engineering
Semantic annotation framework to manage semantic heterogeneity of process models
CAiSE'06 Proceedings of the 18th international conference on Advanced Information Systems Engineering
Supporting Ontology-Based Semantic Annotation of Business Processes with Automated Suggestions
International Journal of Information System Modeling and Design
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Enterprise/business process models that represent knowledge of business processes are generally designed for particular applications in a range of different enterprises. It is a considerable challenge to manage the knowledge of processes that are distributed throughout many different information systems, due to the heterogeneity of the process models used. In this paper, the authors present a framework for semantic annotation that tackles the problem of the heterogeneity of distributed process models to facilitate management of process knowledge. The feasibility of the approach is demonstrated by means of exemplar studies, and a comprehensive empirical evaluation is used to validate the authors' approach.