Publication
Providing packages of relevant ATM information: An ontology-based approach
https://www.sintef.no/en/publications/publication/?pubid=1842235
Audun Vennesland
Research Scientist
Audun Vennesland
Research Scientist
Phone:
928 94 418
Email:
Unit:
SINTEF Digital
Department:
Software Engineering, Safety and Security
Office:
Trondheim
Publications and responsibilities
Publication
Dataintegrasjon
https://www.sintef.no/en/publications/publication/?pubid=1754598
Publication
Towards a semantic matchmaking algorithm for capacity exchange in manufacturing supply chains
https://www.sintef.no/en/publications/publication/?pubid=1777876
Year
2019
Type
Academic chapter/article/Conference paper
Publication
Matching ontologies for air traffic management: A comparison and reference alignment of the AIRM and NASA ATM ontologies
https://www.sintef.no/en/publications/publication/?pubid=1775288
Publication
Matching Ontologies for Air Traffic Management: A Comparison and Reference Alignment of the AIRM and NASA ATM Ontologies
https://www.sintef.no/en/publications/publication/?pubid=1775283
Publication
Towards a semantic matchmaking algorithm for capacity exchange in manufacturing supply chains
https://www.sintef.no/en/publications/publication/?pubid=1767853
Year
2019
Type
Academic lecture
Publication
The semantic container approach techniques for ontology-based data description and discovery in a decentralized swim knowledge base
https://www.sintef.no/en/publications/publication/?pubid=1805740
Publication
The Semantic Container Approach: Techniques for ontology-based data description and discovery in a decentralized SWIM knowledge base
https://www.sintef.no/en/publications/publication/?pubid=1647289
Publication
Automated Compliance Verification in ATM Using Principles from Ontology Matching
https://www.sintef.no/en/publications/publication/?pubid=1647283
Publication
Towards Scalability Guidelines for Semantic Data Container Management
https://www.sintef.no/en/publications/publication/?pubid=1585429
Semantic container management is a promising approach to organize data. However, the scalability of this approach is challenging. By scalability in this paper, we mean the expressivity and size of the semantic data containers we can handle, given a suitable quality threshold. In this paper, we...